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The task is to identify if the occurrences of w in the two contexts correspond to the same meaning or not.\n\nXL-WiC provides dev and test sets in the following 12 languages:\n\nBulgarian (BG)\nDanish (DA)\nGerman (DE)\nEstonian (ET)\nFarsi (FA)\nFrench (FR)\nCroatian (HR)\nItalian (IT)\nJapanese (JA)\nKorean (KO)\nDutch (NL)\nChinese (ZH)\nand training sets in the following 3 languages:\n\nGerman (DE)\nFrench (FR)\nItalian (IT)\n", "citation": "@inproceedings{raganato-etal-2020-xl-wic,\n  title={XL-WiC: A Multilingual Benchmark for Evaluating Semantic Contextualization},\n  author={Raganato, Alessandro and Pasini, Tommaso and Camacho-Collados, Jose and Pilehvar, Mohammad Taher},\n  booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},\n  pages={7193--7206},\n  year={2020}\n}\n", "homepage": "https://pilehvar.github.io/xlwic/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context_1": {"dtype": "string", "id": null, "_type": "Value"}, "context_2": {"dtype": "string", "id": null, "_type": "Value"}, "target_word": {"dtype": "string", "id": null, "_type": "Value"}, "pos": {"dtype": "string", "id": null, "_type": "Value"}, "target_word_location_1": {"char_start": {"dtype": "int32", "id": null, "_type": "Value"}, "char_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "target_word_location_2": {"char_start": {"dtype": "int32", "id": null, "_type": "Value"}, "char_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "language": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "xlwic", "config_name": "xlwic_en_hr", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 733287, "num_examples": 5428, "dataset_name": "xlwic"}, "validation": {"name": "validation", "num_bytes": 16877, "num_examples": 104, "dataset_name": "xlwic"}, "test": {"name": "test", "num_bytes": 66694, "num_examples": 408, "dataset_name": "xlwic"}}, "download_checksums": {"https://pilehvar.github.io/xlwic/data/xlwic_datasets.zip": {"num_bytes": 18748158, "checksum": "40d12d338c90937eab820f24206c06d58b21d996b1d5c7bf69b3f8c65cf7eaff"}}, "download_size": 18748158, "post_processing_size": null, "dataset_size": 816858, "size_in_bytes": 19565016}, "xlwic_en_da": {"description": "A system's task on any of the XL-WiC datasets is to identify the intended meaning of a word in a context of a given language. XL-WiC is framed as a binary classification task. Each instance in XL-WiC has a target word w, either a verb or a noun, for which two contexts are provided. Each of these contexts triggers a specific meaning of w. The task is to identify if the occurrences of w in the two contexts correspond to the same meaning or not.\n\nXL-WiC provides dev and test sets in the following 12 languages:\n\nBulgarian (BG)\nDanish (DA)\nGerman (DE)\nEstonian (ET)\nFarsi (FA)\nFrench (FR)\nCroatian (HR)\nItalian (IT)\nJapanese (JA)\nKorean (KO)\nDutch (NL)\nChinese (ZH)\nand training sets in the following 3 languages:\n\nGerman (DE)\nFrench (FR)\nItalian (IT)\n", "citation": "@inproceedings{raganato-etal-2020-xl-wic,\n  title={XL-WiC: A Multilingual Benchmark for Evaluating Semantic Contextualization},\n  author={Raganato, Alessandro and Pasini, Tommaso and Camacho-Collados, Jose and Pilehvar, Mohammad Taher},\n  booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},\n  pages={7193--7206},\n  year={2020}\n}\n", "homepage": "https://pilehvar.github.io/xlwic/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context_1": {"dtype": "string", "id": null, "_type": "Value"}, "context_2": {"dtype": "string", "id": null, "_type": "Value"}, "target_word": {"dtype": "string", "id": null, "_type": "Value"}, "pos": {"dtype": "string", "id": null, "_type": "Value"}, "target_word_location_1": {"char_start": {"dtype": "int32", "id": null, "_type": "Value"}, "char_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "target_word_location_2": {"char_start": {"dtype": "int32", "id": null, "_type": "Value"}, "char_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "language": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "xlwic", "config_name": "xlwic_en_da", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 733287, "num_examples": 5428, "dataset_name": "xlwic"}, "validation": {"name": "validation", "num_bytes": 198876, "num_examples": 852, "dataset_name": "xlwic"}, "test": {"name": "test", "num_bytes": 800224, "num_examples": 3406, "dataset_name": "xlwic"}}, "download_checksums": {"https://pilehvar.github.io/xlwic/data/xlwic_datasets.zip": {"num_bytes": 18748158, "checksum": "40d12d338c90937eab820f24206c06d58b21d996b1d5c7bf69b3f8c65cf7eaff"}}, "download_size": 18748158, "post_processing_size": null, "dataset_size": 1732387, "size_in_bytes": 20480545}, "xlwic_en_nl": {"description": "A system's task on any of the XL-WiC datasets is to identify the intended meaning of a word in a context of a given language. XL-WiC is framed as a binary classification task. Each instance in XL-WiC has a target word w, either a verb or a noun, for which two contexts are provided. Each of these contexts triggers a specific meaning of w. The task is to identify if the occurrences of w in the two contexts correspond to the same meaning or not.\n\nXL-WiC provides dev and test sets in the following 12 languages:\n\nBulgarian (BG)\nDanish (DA)\nGerman (DE)\nEstonian (ET)\nFarsi (FA)\nFrench (FR)\nCroatian (HR)\nItalian (IT)\nJapanese (JA)\nKorean (KO)\nDutch (NL)\nChinese (ZH)\nand training sets in the following 3 languages:\n\nGerman (DE)\nFrench (FR)\nItalian (IT)\n", "citation": "@inproceedings{raganato-etal-2020-xl-wic,\n  title={XL-WiC: A Multilingual Benchmark for Evaluating Semantic Contextualization},\n  author={Raganato, Alessandro and Pasini, Tommaso and Camacho-Collados, Jose and Pilehvar, Mohammad Taher},\n  booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},\n  pages={7193--7206},\n  year={2020}\n}\n", "homepage": "https://pilehvar.github.io/xlwic/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context_1": {"dtype": "string", "id": null, "_type": "Value"}, "context_2": {"dtype": "string", "id": null, "_type": "Value"}, "target_word": {"dtype": "string", "id": null, "_type": "Value"}, "pos": {"dtype": "string", "id": null, "_type": "Value"}, "target_word_location_1": {"char_start": {"dtype": "int32", "id": null, "_type": "Value"}, "char_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "target_word_location_2": {"char_start": {"dtype": "int32", "id": null, "_type": "Value"}, "char_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "language": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "xlwic", "config_name": "xlwic_en_nl", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 733287, "num_examples": 5428, "dataset_name": "xlwic"}, "validation": {"name": "validation", "num_bytes": 40702, "num_examples": 250, "dataset_name": "xlwic"}, "test": {"name": "test", "num_bytes": 163964, "num_examples": 1004, "dataset_name": "xlwic"}}, "download_checksums": {"https://pilehvar.github.io/xlwic/data/xlwic_datasets.zip": {"num_bytes": 18748158, "checksum": "40d12d338c90937eab820f24206c06d58b21d996b1d5c7bf69b3f8c65cf7eaff"}}, "download_size": 18748158, "post_processing_size": null, "dataset_size": 937953, "size_in_bytes": 19686111}, "xlwic_en_et": {"description": "A system's task on any of the XL-WiC datasets is to identify the intended meaning of a word in a context of a given language. 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The task is to identify if the occurrences of w in the two contexts correspond to the same meaning or not.\n\nXL-WiC provides dev and test sets in the following 12 languages:\n\nBulgarian (BG)\nDanish (DA)\nGerman (DE)\nEstonian (ET)\nFarsi (FA)\nFrench (FR)\nCroatian (HR)\nItalian (IT)\nJapanese (JA)\nKorean (KO)\nDutch (NL)\nChinese (ZH)\nand training sets in the following 3 languages:\n\nGerman (DE)\nFrench (FR)\nItalian (IT)\n", "citation": "@inproceedings{raganato-etal-2020-xl-wic,\n  title={XL-WiC: A Multilingual Benchmark for Evaluating Semantic Contextualization},\n  author={Raganato, Alessandro and Pasini, Tommaso and Camacho-Collados, Jose and Pilehvar, Mohammad Taher},\n  booktitle={Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)},\n  pages={7193--7206},\n  year={2020}\n}\n", "homepage": "https://pilehvar.github.io/xlwic/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context_1": {"dtype": "string", "id": null, "_type": "Value"}, "context_2": {"dtype": "string", "id": null, "_type": "Value"}, "target_word": {"dtype": "string", "id": null, "_type": "Value"}, "pos": {"dtype": "string", "id": null, "_type": "Value"}, "target_word_location_1": {"char_start": {"dtype": "int32", "id": null, "_type": "Value"}, "char_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "target_word_location_2": {"char_start": {"dtype": "int32", "id": null, "_type": "Value"}, "char_end": {"dtype": "int32", "id": null, "_type": "Value"}}, "language": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "xlwic", "config_name": "xlwic_en_et", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 733287, "num_examples": 5428, "dataset_name": "xlwic"}, "validation": {"name": "validation", "num_bytes": 16685, "num_examples": 98, "dataset_name": "xlwic"}, "test": {"name": "test", "num_bytes": 67034, "num_examples": 390, "dataset_name": "xlwic"}}, "download_checksums": {"https://pilehvar.github.io/xlwic/data/xlwic_datasets.zip": {"num_bytes": 18748158, "checksum": "40d12d338c90937eab820f24206c06d58b21d996b1d5c7bf69b3f8c65cf7eaff"}}, "download_size": 18748158, "post_processing_size": null, "dataset_size": 817006, "size_in_bytes": 19565164}, "xlwic_en_fa": {"description": "A system's task on any of the XL-WiC datasets is to identify the intended meaning of a word in a context of a given language. 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