Ссылки:
presupposition_all_n_presupposition
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_all_n_presupposition')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'all_n_presupposition' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_both_presupposition
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_both_presupposition')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'both_presupposition' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
пресуппозиция_изменения_состояния
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_change_of_state')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'change_of_state' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_cleft_existence
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_cleft_existence')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'cleft_existence' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_cleft_uniqueness
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_cleft_uniqueness')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'cleft_uniqueness' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_only_presupposition
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_only_presupposition')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'only_presupposition' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_possessed_definites_existence
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_existence')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'possessed_definites_existence' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_possessed_definites_uniqueness
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_uniqueness')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'possessed_definites_uniqueness' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_question_presupposition
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/presupposition_question_presupposition')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'question_presupposition' | 1900 г. |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
impliture_connectives
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/implicature_connectives')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'connectives' | 1200 |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
impliture_gradable_adjective
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/implicature_gradable_adjective')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'gradable_adjective' | 1200 |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
impliture_gradable_verb
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/implicature_gradable_verb')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'gradable_verb' | 1200 |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
impliture_modals
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/implicature_modals')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'modals' | 1200 |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
impliture_numerals_10_100
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/implicature_numerals_10_100')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'numerals_10_100' | 1200 |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
impliture_numerals_2_3
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/implicature_numerals_2_3')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'numerals_2_3' | 1200 |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
impliture_quantifiers
Используйте следующую команду, чтобы загрузить этот набор данных в TFDS:
ds = tfds.load('huggingface:imppres/implicature_quantifiers')
- Описание :
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- Лицензия : Creative Commons Attribution-NonCommercial 4.0 Международная общественная лицензия.
- Версия : 1.1.0
- Расколы :
| Расколоть | Примеры |
|---|---|
'quantifiers' | 1200 |
- Функции :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}