{ "default": { "description": "The Multi-Genre Natural Language Inference (MultiNLI) corpus is a\ncrowd-sourced collection of 433k sentence pairs annotated with textual\nentailment information. The corpus is modeled on the SNLI corpus, but differs in\nthat covers a range of genres of spoken and written text, and supports a\ndistinctive cross-genre generalization evaluation. The corpus served as the\nbasis for the shared task of the RepEval 2017 Workshop at EMNLP in Copenhagen.\n", "citation": "@InProceedings{N18-1101,\n author = {Williams, Adina\n and Nangia, Nikita\n and Bowman, Samuel},\n title = {A Broad-Coverage Challenge Corpus for\n Sentence Understanding through Inference},\n booktitle = {Proceedings of the 2018 Conference of\n the North American Chapter of the\n Association for Computational Linguistics:\n Human Language Technologies, Volume 1 (Long\n Papers)},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n pages = {1112--1122},\n location = {New Orleans, Louisiana},\n url = {http://aclweb.org/anthology/N18-1101}\n}\n", "homepage": "https://www.nyu.edu/projects/bowman/multinli/", "license": "", "features": { "promptID": { "dtype": "int32", "_type": "Value" }, "pairID": { "dtype": "string", "_type": "Value" }, "premise": { "dtype": "string", "_type": "Value" }, "premise_binary_parse": { "dtype": "string", "_type": "Value" }, "premise_parse": { "dtype": "string", "_type": "Value" }, "hypothesis": { "dtype": "string", "_type": "Value" }, "hypothesis_binary_parse": { "dtype": "string", "_type": "Value" }, "hypothesis_parse": { "dtype": "string", "_type": "Value" }, "genre": { "dtype": "string", "_type": "Value" }, "label": { "names": [ "entailment", "neutral", "contradiction" ], "_type": "ClassLabel" } }, "builder_name": "multi_nli", "dataset_name": "multi_nli", "config_name": "default", "version": { "version_str": "0.0.0", "major": 0, "minor": 0, "patch": 0 }, "splits": { "train": { "name": "train", "num_bytes": 410210306, "num_examples": 392702, "dataset_name": null }, "validation_matched": { "name": "validation_matched", "num_bytes": 10063907, "num_examples": 9815, "dataset_name": null }, "validation_mismatched": { "name": "validation_mismatched", "num_bytes": 10610189, "num_examples": 9832, "dataset_name": null } }, "download_size": 224005223, "dataset_size": 430884402, "size_in_bytes": 654889625 } }