Correct the file used for the train partition

dataset_infos.json

@@ -1 +1 @@
-{"named-timexes": {"description": "This is a dataset annotated for _named temporal expression_ chunks.\n\nThe\ncommonest temporal expressions typically\ncontain date and time words, like April or\nhours. Research into recognising and interpreting these typical expressions is mature in many languages. However, there is\na class of expressions that are less typical,\nvery varied, and difficult to automatically\ninterpret. These indicate dates and times,\nbut are harder to detect because they often do not contain time words and are not\nused frequently enough to appear in conventional temporally-annotated corpora \u2013\nfor example *Michaelmas* or *Vasant Panchami*.\n\nFor more details see [https://aclanthology.org/R13-1015.pdf](https://aclanthology.org/R13-1015.pdf)\n", "citation": "@inproceedings{brucato-etal-2013-recognising,\n    title = \"Recognising and Interpreting Named Temporal Expressions\",\n    author = \"Brucato, Matteo  and\n      Derczynski, Leon  and\n      Llorens, Hector  and\n      Bontcheva, Kalina  and\n      Jensen, Christian S.\",\n    booktitle = \"Proceedings of the International Conference Recent Advances in Natural Language Processing {RANLP} 2013\",\n    month = sep,\n    year = \"2013\",\n    address = \"Hissar, Bulgaria\",\n    publisher = \"INCOMA Ltd. Shoumen, BULGARIA\",\n    url = \"https://aclanthology.org/R13-1015\",\n    pages = \"113--121\",\n}\n", "homepage": "https://aclanthology.org/R13-1015.pdf", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ntimex_tags": {"feature": {"num_classes": 2, "names": ["O", "T"], "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "named_timexes", "config_name": "named-timexes", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 509424, "num_examples": 965, "dataset_name": "named_timexes"}, "test": {"name": "test", "num_bytes": 509424, "num_examples": 965, "dataset_name": "named_timexes"}}, "download_checksums": {"http://www.derczynski.com/resources/named_timex.tar.bz2": {"num_bytes": 339205, "checksum": "90e9f016602c873783862dff9a83bb0786a47f48c0dab6e4d540c4082b9a0bfe"}}, "download_size": 339205, "post_processing_size": null, "dataset_size": 1018848, "size_in_bytes": 1358053}}
+{"named-timexes": {"description": "This is a dataset annotated for _named temporal expression_ chunks.\n\nThe\ncommonest temporal expressions typically\ncontain date and time words, like April or\nhours. Research into recognising and interpreting these typical expressions is mature in many languages. However, there is\na class of expressions that are less typical,\nvery varied, and difficult to automatically\ninterpret. These indicate dates and times,\nbut are harder to detect because they often do not contain time words and are not\nused frequently enough to appear in conventional temporally-annotated corpora \u2013\nfor example *Michaelmas* or *Vasant Panchami*.\n\nFor more details see [https://aclanthology.org/R13-1015.pdf](https://aclanthology.org/R13-1015.pdf)\n", "citation": "@inproceedings{brucato-etal-2013-recognising,\n    title = \"Recognising and Interpreting Named Temporal Expressions\",\n    author = \"Brucato, Matteo  and\n      Derczynski, Leon  and\n      Llorens, Hector  and\n      Bontcheva, Kalina  and\n      Jensen, Christian S.\",\n    booktitle = \"Proceedings of the International Conference Recent Advances in Natural Language Processing {RANLP} 2013\",\n    month = sep,\n    year = \"2013\",\n    address = \"Hissar, Bulgaria\",\n    publisher = \"INCOMA Ltd. Shoumen, BULGARIA\",\n    url = \"https://aclanthology.org/R13-1015\",\n    pages = \"113--121\",\n}\n", "homepage": "https://aclanthology.org/R13-1015.pdf", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ntimex_tags": {"feature": {"num_classes": 2, "names": ["O", "T"], "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "named_timexes", "config_name": "named-timexes", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1484945, "num_examples": 2955, "dataset_name": "named_timexes"}, "test": {"name": "test", "num_bytes": 509424, "num_examples": 965, "dataset_name": "named_timexes"}}, "download_checksums": {"http://www.derczynski.com/resources/named_timex.tar.bz2": {"num_bytes": 339205, "checksum": "90e9f016602c873783862dff9a83bb0786a47f48c0dab6e4d540c4082b9a0bfe"}}, "download_size": 339205, "post_processing_size": null, "dataset_size": 1994369, "size_in_bytes": 2333574}}

named_timexes.py

@@ -114,7 +114,7 @@ class NamedTimexes(datasets.GeneratorBasedBuilder):
         }
 
         return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["test"]}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_files["train"]}),
             datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": data_files["test"]}),
         ]