TFDS اکنون از فرمت Croissant 🥐 پشتیبانی می کند! برای دانستن بیشتر مستندات را بخوانید.

این صفحه به‌وسیله ‏Cloud Translation API‏ ترجمه شده است.

تحت تاثیر قرار دادن

منابع:

پیش فرض_همه_ن_پیش فرض

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_all_n_presupposition')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیمات :

شکاف	مثال ها
`'all_n_presupposition'`	1900

امکانات :

{
    "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"
    }
}

پیش فرض_هم_پیش فرض

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_both_presupposition')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیمات :

شکاف	مثال ها
`'both_presupposition'`	1900

امکانات :

{
    "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"
    }
}

پیش فرض_تغییر_حالت

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_change_of_state')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیمات :

شکاف	مثال ها
`'change_of_state'`	1900

امکانات :

{
    "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"
    }
}

پیش فرض_شکاف_وجود

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_cleft_existence')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیمات :

شکاف	مثال ها
`'cleft_existence'`	1900

امکانات :

{
    "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"
    }
}

پیش فرض_شکاف_یکتا بودن

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_cleft_uniqueness')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'cleft_uniqueness'`	1900

امکانات :

{
    "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"
    }
}

پیش فرض_فقط_پیش فرض

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_only_presupposition')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'only_presupposition'`	1900

امکانات :

{
    "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"
    }
}

پیش فرض_دارای_تعریف_وجود

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_existence')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'possessed_definites_existence'`	1900

امکانات :

{
    "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"
    }
}

پیش فرض_دارای_تعریف_بیگانه بودن

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_uniqueness')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'possessed_definites_uniqueness'`	1900

امکانات :

{
    "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"
    }
}

پیش فرض_سوال_پیش فرض

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/presupposition_question_presupposition')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'question_presupposition'`	1900

امکانات :

{
    "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"
    }
}

implicature_connectives

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/implicature_connectives')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'connectives'`	1200

امکانات :

{
    "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"
    }
}

implicature_gradable_adjective

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/implicature_gradable_adjective')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'gradable_adjective'`	1200

امکانات :

{
    "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"
    }
}

implicature_gradable_verb

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/implicature_gradable_verb')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'gradable_verb'`	1200

امکانات :

{
    "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"
    }
}

implicature_modals

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/implicature_modals')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'modals'`	1200

امکانات :

{
    "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"
    }
}

implicature_numerals_10_100

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/implicature_numerals_10_100')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'numerals_10_100'`	1200

امکانات :

{
    "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"
    }
}

implicature_numerals_2_3

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/implicature_numerals_2_3')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'numerals_2_3'`	1200

امکانات :

{
    "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"
    }
}

implicature_quantifiers

برای بارگذاری این مجموعه داده در TFDS از دستور زیر استفاده کنید:

ds = tfds.load('huggingface:imppres/implicature_quantifiers')

شرح :

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.

مجوز : Creative Commons Attribution-NonCommercial 4.0 International Public License
نسخه : 1.1.0
تقسیم ها :

شکاف	مثال ها
`'quantifiers'`	1200

امکانات :

{
    "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"
    }
}