مراجع:
adjunct_island
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/adjunct_island')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
anaphor_gender_agreement
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/anaphor_gender_agreement')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
anaphor_number_agreement
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/anaphor_number_agreement')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
animate_subject_passive
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/animate_subject_passive')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
animate_subject_trans
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/animate_subject_trans')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
مسبب
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/causative')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
complex_NP_island
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/complex_NP_island')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
format_structure_constraint_complex_left_branch
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/coordinate_structure_constraint_complex_left_branch')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
format_structure_constraint_object_extraction
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/coordinate_structure_constraint_object_extraction')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المحدد_اسم_الاتفاقية_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المحدد_اسم_الاتفاقية_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المحدد_اسم_الاتفاقية_غير المنتظمة_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_irregular_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المحدد_اسم_الاتفاقية_غير المنتظمة_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_irregular_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المحدد_اسم_الاتفاقية_مع_adj_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المحدد_اسم_الاتفاقية_مع_adj_irregular_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_irregular_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المحدد_اسم_الاتفاقية_مع_adj_irregular_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_irregular_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المحدد_اسم_الاتفاقية_مع_الصفة_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adjective_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Distributer_agreement_relational_non
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/distractor_agreement_relational_noun')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Distributer_agreement_relative_clause
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/distractor_agreement_relative_clause')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
drop_argument
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/drop_argument')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
علامة القطع_n_bar_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/ellipsis_n_bar_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
علامة الحذف_n_bar_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/ellipsis_n_bar_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
الوجودي_هناك_كائن_رفع
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/existential_there_object_raising')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
الوجودي_هناك_الكميات_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/existential_there_quantifiers_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
الوجودي_هناك_الكميات_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/existential_there_quantifiers_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
الوجودي_هناك_موضوع_رفع
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/existential_there_subject_raising')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Expletive_it_object_ising
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/expletive_it_object_raising')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
غير مبدئي
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/inchoative')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
لازمة
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/intransitive')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
غير منتظم_الماضي_الجزئي_الصفات
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/irregular_past_participle_adjectives')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
غير منتظم_الماضي_الفعال_الأفعال
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/irregular_past_participle_verbs')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
غير منتظم_جمع_موضوع_فعل_اتفاقية_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/irregular_plural_subject_verb_agreement_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
غير منتظم_جمع_موضوع_فعل_اتفاقية_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/irregular_plural_subject_verb_agreement_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
left_branch_island_echo_question
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/left_branch_island_echo_question')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
left_branch_island_simple_question
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/left_branch_island_simple_question')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Matrix_question_npi_license_present
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/matrix_question_npi_licensor_present')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
npi_present_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/npi_present_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
npi_present_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/npi_present_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
فقط_npi_licenser_present
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/only_npi_licensor_present')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
فقط_npi_scope
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/only_npi_scope')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
passive_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/passive_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
passive_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/passive_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المبدأ_A_c_command
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/principle_A_c_command')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المبدأ_أ_الحالة_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/principle_A_case_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المبدأ_أ_الحالة_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/principle_A_case_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المبدأ_A_domain_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المبدأ_A_domain_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المبدأ_A_domain_3
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_3')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
المبدأ_أ_إعادة الإعمار
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/principle_A_reconstruction')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Regular_plural_subject_verb_agreement_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/regular_plural_subject_verb_agreement_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Regular_plural_subject_verb_agreement_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/regular_plural_subject_verb_agreement_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Senential_negation_npi_license_present
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/sentential_negation_npi_licensor_present')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Senential_negation_npi_scope
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/sentential_negation_npi_scope')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Senential_subject_island
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/sentential_subject_island')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
superlative_quantifiers_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/superlative_quantifiers_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
superlative_quantifiers_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/superlative_quantifiers_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
strong_vs_ising_1
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/tough_vs_raising_1')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
strong_vs_ising_2
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/tough_vs_raising_2')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
متعد
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/transitive')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_island
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/wh_island')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_object_gap
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_object_gap')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_subject_gap
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_subject_gap')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_subject_gap_long_distance
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_subject_gap_long_distance')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_no_gap
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_no_gap')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_no_gap_long_distance
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_no_gap_long_distance')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_with_gap
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_with_gap')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_with_gap_long_distance
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_with_gap_long_distance')
- وصف :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- الترخيص : لا يوجد ترخيص معروف
- الإصدار : 0.1.0
- الإنشقاقات :
| ينقسم | أمثلة |
|---|---|
'train' | 1000 |
- سمات :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}