Datasets:
polemo2

{"in": {"description": "The PolEmo2.0 is a set of online reviews from medicine and hotels domains. The task is to predict the sentiment of a review. There are two separate test sets, to allow for in-domain (medicine and hotels) as well as out-of-domain (products and university) validation.\n", "citation": "@inproceedings{kocon-etal-2019-multi,\ntitle = \"Multi-Level Sentiment Analysis of {P}ol{E}mo 2.0: Extended Corpus of Multi-Domain Consumer Reviews\",\nauthor = \"Koco{'n}, Jan and\nMi{\\l}kowski, Piotr and\nZa{'s}ko-Zieli{'n}ska, Monika\",\nbooktitle = \"Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)\",\nmonth = nov,\nyear = \"2019\",\naddress = \"Hong Kong, China\",\npublisher = \"Association for Computational Linguistics\",\nurl = \"https://www.aclweb.org/anthology/K19-1092\",\ndoi = \"10.18653/v1/K19-1092\",\npages = \"980--991\",\n}\n", "homepage": "https://clarin-pl.eu/dspace/handle/11321/710", "license": "CC BY-NC-SA 4.0", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "target": {"num_classes": 4, "names": ["__label__meta_amb", "__label__meta_minus_m", "__label__meta_plus_m", "__label__meta_zero"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polemo2", "config_name": "in", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4810215, "num_examples": 5783, "dataset_name": "polemo2"}, "test": {"name": "test", "num_bytes": 582052, "num_examples": 722, "dataset_name": "polemo2"}, "validation": {"name": "validation", "num_bytes": 593530, "num_examples": 723, "dataset_name": "polemo2"}}, "download_checksums": {"https://klejbenchmark.com/static/data/klej_polemo2.0-in.zip": {"num_bytes": 2350339, "checksum": "ec9ccfa232686081577e6c250c79c028411076e84db60d4cd192f9a567a2cb96"}}, "download_size": 2350339, "post_processing_size": null, "dataset_size": 5985797, "size_in_bytes": 8336136}, "out": {"description": "The PolEmo2.0 is a set of online reviews from medicine and hotels domains. The task is to predict the sentiment of a review. There are two separate test sets, to allow for in-domain (medicine and hotels) as well as out-of-domain (products and university) validation.\n", "citation": "@inproceedings{kocon-etal-2019-multi,\ntitle = \"Multi-Level Sentiment Analysis of {P}ol{E}mo 2.0: Extended Corpus of Multi-Domain Consumer Reviews\",\nauthor = \"Koco{'n}, Jan and\nMi{\\l}kowski, Piotr and\nZa{'s}ko-Zieli{'n}ska, Monika\",\nbooktitle = \"Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)\",\nmonth = nov,\nyear = \"2019\",\naddress = \"Hong Kong, China\",\npublisher = \"Association for Computational Linguistics\",\nurl = \"https://www.aclweb.org/anthology/K19-1092\",\ndoi = \"10.18653/v1/K19-1092\",\npages = \"980--991\",\n}\n", "homepage": "https://clarin-pl.eu/dspace/handle/11321/710", "license": "CC BY-NC-SA 4.0", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "target": {"num_classes": 4, "names": ["__label__meta_amb", "__label__meta_minus_m", "__label__meta_plus_m", "__label__meta_zero"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polemo2", "config_name": "out", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4810215, "num_examples": 5783, "dataset_name": "polemo2"}, "test": {"name": "test", "num_bytes": 309790, "num_examples": 494, "dataset_name": "polemo2"}, "validation": {"name": "validation", "num_bytes": 310977, "num_examples": 494, "dataset_name": "polemo2"}}, "download_checksums": {"https://klejbenchmark.com/static/data/klej_polemo2.0-out.zip": {"num_bytes": 2139891, "checksum": "202668a59ce18cf476a7d3a8c76a802fe1eeaa869caa687313c43246988046ba"}}, "download_size": 2139891, "post_processing_size": null, "dataset_size": 5430982, "size_in_bytes": 7570873}}