Datasets:
pragmeval

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EmoBank excels with a bi-perspectival and bi-representational design. On the one hand, we distinguish between writer{'}s and reader{'}s emotions, on the other hand, a subset of the corpus complements dimensional VAD annotations with categorical ones based on Basic Emotions. We find evidence for the supremacy of the reader{'}s perspective in terms of IAA and rating intensity, and achieve close-to-human performance when mapping between dimensional and categorical formats.\",\n }\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["low", "high"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "emobank-arousal", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 567660, "num_examples": 5470, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 71221, "num_examples": 684, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 69276, "num_examples": 683, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 708157, "size_in_bytes": 6038881}, "switchboard": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n@inproceedings{Godfrey:1992:STS:1895550.1895693,\n author = {Godfrey, John J. and Holliman, Edward C. and McDaniel, Jane},\n title = {SWITCHBOARD: Telephone Speech Corpus for Research and Development},\n booktitle = {Proceedings of the 1992 IEEE International Conference on Acoustics, Speech and Signal Processing - Volume 1},\n series = {ICASSP'92},\n year = {1992},\n isbn = {0-7803-0532-9},\n location = {San Francisco, California},\n pages = {517--520},\n numpages = {4},\n url = {http://dl.acm.org/citation.cfm?id=1895550.1895693},\n acmid = {1895693},\n publisher = {IEEE Computer Society},\n address = {Washington, DC, USA},\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 41, "names": ["Response Acknowledgement", "Uninterpretable", "Or-Clause", "Reject", "Statement-non-opinion", "3rd-party-talk", "Repeat-phrase", "Hold Before Answer/Agreement", "Signal-non-understanding", "Offers, Options Commits", "Agree/Accept", "Dispreferred Answers", "Hedge", "Action-directive", "Tag-Question", "Self-talk", "Yes-No-Question", "Rhetorical-Question", "No Answers", "Open-Question", "Conventional-closing", "Other Answers", "Acknowledge (Backchannel)", "Wh-Question", "Declarative Wh-Question", "Thanking", "Yes Answers", "Affirmative Non-yes Answers", "Declarative Yes-No-Question", "Backchannel in Question Form", "Apology", "Downplayer", "Conventional-opening", "Collaborative Completion", "Summarize/Reformulate", "Negative Non-no Answers", "Statement-opinion", "Appreciation", "Other", "Quotation", "Maybe/Accept-part"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "switchboard", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1021220, "num_examples": 18930, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 116058, "num_examples": 2113, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 34013, "num_examples": 649, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 1171291, "size_in_bytes": 6502015}, "persuasiveness-eloquence": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n@inproceedings{Persuasion2018Ng,\n title = \"Give Me More Feedback: Annotating Argument Persuasiveness and Related Attributes in Student Essays\",\n author = \"Carlile, Winston and\n Gurrapadi, Nishant and\n Ke, Zixuan and\n Ng, Vincent\",\n booktitle = \"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)\",\n month = jul,\n year = \"2018\",\n address = \"Melbourne, Australia\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/P18-1058\",\n pages = \"621--631\",\n abstract = \"While argument persuasiveness is one of the most important dimensions of argumentative essay quality, it is relatively little studied in automated essay scoring research. Progress on scoring argument persuasiveness is hindered in part by the scarcity of annotated corpora. We present the first corpus of essays that are simultaneously annotated with argument components, argument persuasiveness scores, and attributes of argument components that impact an argument{'}s persuasiveness. This corpus could trigger the development of novel computational models concerning argument persuasiveness that provide useful feedback to students on why their arguments are (un)persuasive in addition to how persuasive they are.\",\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["low", "high"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "persuasiveness-eloquence", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 153946, "num_examples": 725, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 19376, "num_examples": 91, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 18379, "num_examples": 90, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 191701, "size_in_bytes": 5522425}, "mrda": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n@inproceedings{shriberg2004icsi,\n title={The ICSI meeting recorder dialog act (MRDA) corpus},\n author={Shriberg, Elizabeth and Dhillon, Raj and Bhagat, Sonali and Ang, Jeremy and Carvey, Hannah},\n booktitle={Proceedings of the 5th SIGdial Workshop on Discourse and Dialogue at HLT-NAACL 2004},\n year={2004}\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 51, "names": ["Declarative-Question", "Statement", "Reject", "Or-Clause", "3rd-party-talk", "Continuer", "Hold Before Answer/Agreement", "Assessment/Appreciation", "Signal-non-understanding", "Floor Holder", "Sympathy", "Dispreferred Answers", "Reformulate/Summarize", "Exclamation", "Interrupted/Abandoned/Uninterpretable", "Expansions of y/n Answers", "Action-directive", "Tag-Question", "Accept", "Rhetorical-question Continue", "Self-talk", "Rhetorical-Question", "Yes-No-question", "Open-Question", "Rising Tone", "Other Answers", "Commit", "Wh-Question", "Repeat", "Follow Me", "Thanking", "Offer", "About-task", "Reject-part", "Affirmative Non-yes Answers", "Apology", "Downplayer", "Humorous Material", "Accept-part", "Collaborative Completion", "Mimic Other", "Understanding Check", "Misspeak Self-Correction", "Or-Question", "Topic Change", "Negative Non-no Answers", "Floor Grabber", "Correct-misspeaking", "Maybe", "Acknowledge-answer", "Defending/Explanation"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "mrda", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 963913, "num_examples": 14484, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 111813, "num_examples": 1630, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 419797, "num_examples": 6459, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 1495523, "size_in_bytes": 6826247}, "gum": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n@Article{Zeldes2017,\n author = {Amir Zeldes},\n title = {The {GUM} Corpus: Creating Multilayer Resources in the Classroom},\n journal = {Language Resources and Evaluation},\n year = {2017},\n volume = {51},\n number = {3},\n pages = {581--612},\n doi = {http://dx.doi.org/10.1007/s10579-016-9343-x}\n }\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language 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"num_examples": 1700, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 35405, "num_examples": 259, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 40334, "num_examples": 248, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 346140, "size_in_bytes": 5676864}, "emergent": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n@inproceedings{Ferreira2016EmergentAN,\n title={Emergent: a novel data-set for stance classification},\n author={William Ferreira and Andreas Vlachos},\n booktitle={HLT-NAACL},\n year={2016}\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n 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Progress on scoring argument persuasiveness is hindered in part by the scarcity of annotated corpora. We present the first corpus of essays that are simultaneously annotated with argument components, argument persuasiveness scores, and attributes of argument components that impact an argument{'}s persuasiveness. 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This corpus could trigger the development of novel computational models concerning argument persuasiveness that provide useful feedback to students on why their arguments are (un)persuasive in addition to how persuasive they are.\",\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["low", "high"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "persuasiveness-strength", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 79679, "num_examples": 371, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 10052, "num_examples": 46, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 10225, "num_examples": 46, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 99956, "size_in_bytes": 5430680}, "emobank-dominance": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\"\n @inproceedings{buechel-hahn-2017-emobank,\n title = \"{E}mo{B}ank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis\",\n author = \"Buechel, Sven and\n Hahn, Udo\",\n booktitle = \"Proceedings of the 15th Conference of the {E}uropean Chapter of the Association for Computational Linguistics: Volume 2, Short Papers\",\n month = apr,\n year = \"2017\",\n address = \"Valencia, Spain\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/E17-2092\",\n pages = \"578--585\",\n abstract = \"We describe EmoBank, a corpus of 10k English sentences balancing multiple genres, which we annotated with dimensional emotion metadata in the Valence-Arousal-Dominance (VAD) representation format. 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The main goal of the STAC project is to study the discourse structure of multi-party dialogues in order to understand the linguistic strategies adopted by interlocutors to achieve their conversational goals, especially when these goals are opposed. The STAC corpus is not only a rich source of data on strategic conversation, but also the first corpus that we are aware of that provides full discourse structures for multi-party dialogues. It has other remarkable features that make it an interesting resource for other topics: interleaved threads, creative language, and interactions between linguistic and extra-linguistic contexts.\",\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 18, "names": ["Comment", "Contrast", "Q_Elab", "Parallel", "Explanation", "Narration", "Continuation", "Result", "Acknowledgement", "Alternation", "Question_answer_pair", "Correction", "Clarification_question", "Conditional", "Sequence", "Elaboration", "Background", "no_relation"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "stac", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 645969, "num_examples": 11230, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 71400, "num_examples": 1247, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 70451, "num_examples": 1304, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 787820, "size_in_bytes": 6118544}, "pdtb": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n @inproceedings{prasad-etal-2008-penn,\n title = \"The {P}enn {D}iscourse {T}ree{B}ank 2.0.\",\n author = \"Prasad, Rashmi and\n Dinesh, Nikhil and\n Lee, Alan and\n Miltsakaki, Eleni and\n Robaldo, Livio and\n Joshi, Aravind and\n Webber, Bonnie\",\n booktitle = \"Proceedings of the Sixth International Conference on Language Resources and Evaluation ({LREC}'08)\",\n month = may,\n year = \"2008\",\n address = \"Marrakech, Morocco\",\n publisher = \"European Language Resources Association (ELRA)\",\n url = \"http://www.lrec-conf.org/proceedings/lrec2008/pdf/754_paper.pdf\",\n abstract = \"We present the second version of the Penn Discourse Treebank, PDTB-2.0, describing its lexically-grounded annotations of discourse relations and their two abstract object arguments over the 1 million word Wall Street Journal corpus. We describe all aspects of the annotation, including (a) the argument structure of discourse relations, (b) the sense annotation of the relations, and (c) the attribution of discourse relations and each of their arguments. We list the differences between PDTB-1.0 and PDTB-2.0. We present representative statistics for several aspects of the annotation in the corpus.\",\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 16, "names": ["Synchrony", "Contrast", "Asynchronous", "Conjunction", "List", "Condition", "Pragmatic concession", "Restatement", "Pragmatic cause", "Alternative", "Pragmatic condition", "Pragmatic contrast", "Instantiation", "Exception", "Cause", "Concession"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "pdtb", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2968638, "num_examples": 12907, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 276997, "num_examples": 1204, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 235851, "num_examples": 1085, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 3481486, "size_in_bytes": 8812210}, "persuasiveness-premisetype": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n@inproceedings{Persuasion2018Ng,\n title = \"Give Me More Feedback: Annotating Argument Persuasiveness and Related Attributes in Student Essays\",\n author = \"Carlile, Winston and\n Gurrapadi, Nishant and\n Ke, Zixuan and\n Ng, Vincent\",\n booktitle = \"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)\",\n month = jul,\n year = \"2018\",\n address = \"Melbourne, Australia\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/P18-1058\",\n pages = \"621--631\",\n abstract = \"While argument persuasiveness is one of the most important dimensions of argumentative essay quality, it is relatively little studied in automated essay scoring research. Progress on scoring argument persuasiveness is hindered in part by the scarcity of annotated corpora. We present the first corpus of essays that are simultaneously annotated with argument components, argument persuasiveness scores, and attributes of argument components that impact an argument{'}s persuasiveness. This corpus could trigger the development of novel computational models concerning argument persuasiveness that provide useful feedback to students on why their arguments are (un)persuasive in addition to how persuasive they are.\",\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 8, "names": ["testimony", "warrant", "invented_instance", "common_knowledge", "statistics", "analogy", "definition", "real_example"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "persuasiveness-premisetype", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 122631, "num_examples": 566, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 15920, "num_examples": 71, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 14395, "num_examples": 70, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 152946, "size_in_bytes": 5483670}, "squinky-informativeness": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n@article{DBLP:journals/corr/Lahiri15,\n author = {Shibamouli Lahiri},\n title = {{SQUINKY! A Corpus of Sentence-level Formality, Informativeness,\n and Implicature}},\n journal = {CoRR},\n volume = {abs/1506.02306},\n year = {2015},\n url = {http://arxiv.org/abs/1506.02306},\n timestamp = {Wed, 01 Jul 2015 15:10:24 +0200},\n biburl = {http://dblp.uni-trier.de/rec/bib/journals/corr/Lahiri15},\n bibsource = {dblp computer science bibliography, http://dblp.org}\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["low", "high"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "squinky-informativeness", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 464855, "num_examples": 3719, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 60447, "num_examples": 465, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 56872, "num_examples": 464, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 582174, "size_in_bytes": 5912898}, "persuasiveness-claimtype": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\n@inproceedings{Persuasion2018Ng,\n title = \"Give Me More Feedback: Annotating Argument Persuasiveness and Related Attributes in Student Essays\",\n author = \"Carlile, Winston and\n Gurrapadi, Nishant and\n Ke, Zixuan and\n Ng, Vincent\",\n booktitle = \"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)\",\n month = jul,\n year = \"2018\",\n address = \"Melbourne, Australia\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/P18-1058\",\n pages = \"621--631\",\n abstract = \"While argument persuasiveness is one of the most important dimensions of argumentative essay quality, it is relatively little studied in automated essay scoring research. Progress on scoring argument persuasiveness is hindered in part by the scarcity of annotated corpora. We present the first corpus of essays that are simultaneously annotated with argument components, argument persuasiveness scores, and attributes of argument components that impact an argument{'}s persuasiveness. This corpus could trigger the development of novel computational models concerning argument persuasiveness that provide useful feedback to students on why their arguments are (un)persuasive in addition to how persuasive they are.\",\n}\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["Value", "Fact", "Policy"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "persuasiveness-claimtype", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 31259, "num_examples": 160, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 3803, "num_examples": 20, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 3717, "num_examples": 19, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 38779, "size_in_bytes": 5369503}, "emobank-valence": {"description": "Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics\n", "citation": "\"\n @inproceedings{buechel-hahn-2017-emobank,\n title = \"{E}mo{B}ank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis\",\n author = \"Buechel, Sven and\n Hahn, Udo\",\n booktitle = \"Proceedings of the 15th Conference of the {E}uropean Chapter of the Association for Computational Linguistics: Volume 2, Short Papers\",\n month = apr,\n year = \"2017\",\n address = \"Valencia, Spain\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/E17-2092\",\n pages = \"578--585\",\n abstract = \"We describe EmoBank, a corpus of 10k English sentences balancing multiple genres, which we annotated with dimensional emotion metadata in the Valence-Arousal-Dominance (VAD) representation format. EmoBank excels with a bi-perspectival and bi-representational design. On the one hand, we distinguish between writer{'}s and reader{'}s emotions, on the other hand, a subset of the corpus complements dimensional VAD annotations with categorical ones based on Basic Emotions. We find evidence for the supremacy of the reader{'}s perspective in terms of IAA and rating intensity, and achieve close-to-human performance when mapping between dimensional and categorical formats.\",\n }\n\n@misc{sileo2019discoursebased,\n title={Discourse-Based Evaluation of Language Understanding},\n author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},\n year={2019},\n eprint={1907.08672},\n archivePrefix={arXiv},\n primaryClass={cs.CL}\n}\n", "homepage": "", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["low", "high"], "names_file": null, "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "pragmeval", "config_name": "emobank-valence", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 539652, "num_examples": 5150, "dataset_name": "pragmeval"}, "validation": {"name": "validation", "num_bytes": 62809, "num_examples": 644, "dataset_name": "pragmeval"}, "test": {"name": "test", "num_bytes": 66178, "num_examples": 643, "dataset_name": "pragmeval"}}, "download_checksums": {"https://www.dropbox.com/s/njcy51alkb17sft/pragmeval.zip?dl=1": {"num_bytes": 5330724, "checksum": "89e058b3b58e46e5401cfd91e3b06f7a1cd4421dc0f761bdd7adfe9723237e0b"}}, "download_size": 5330724, "post_processing_size": null, "dataset_size": 668639, "size_in_bytes": 5999363}}