Datasets:

havens2
/

naacl2022

id stringlengths 1 4	tokens sequence	ner_tags sequence
0	[ "References" ]	[ 0 ]
1	[ "Acknowledgments" ]	[ 0 ]
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81	[ "The", "vanilla", "usage", "of", "pre-trained", "encoder-decoders", "for", "MCQA", "is", "to", "reform", "the", "input", "and", "output", "in", "a", "way", "that", "can", "be", "directly", "processed", "by", "a", "encoder-decoder", "model." ]	[ 0, 0, 0, 0, 0, 0, 0, 11, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
82	[ "5.1.1", "Baselines", "Text2Textvanilla" ]	[ 0, 0, 1 ]
83	[ "Table", "2:", "Comparison", "with", "text-to-text", "models." ]	[ 0, 0, 0, 0, 0, 0 ]
84	[ "To", "empirically", "evaluate", "GenMC", "in", "terms", "of", "whether", "it", "better", "exploits", "the", "potential", "of", "pretrained", "encoder-decoder", "models", "for", "MCQA,", "we", "compare", "GenMC", "with", "a", "standard", "text-to-text", "implementation", "and", "with", "a", "variant", "thereof", "for", "analysis." ]	[ 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
85	[ "Text-to-Text", "Models" ]	[ 0, 0 ]
86	[ "5.1", "Main", "Results:", "Comparison", "with" ]	[ 0, 0, 0, 0, 0 ]
87	[ "5", "Experimental", "Results" ]	[ 0, 0, 0 ]
88	[ "For", "each", "model,", "we", "reported", "its", "proportion", "of", "correctly", "answered", "questions", "in", "each", "dataset." ]	[ 0, 0, 0, 0, 0, 0, 7, 8, 8, 8, 8, 0, 0, 0 ]
89	[ "4.3", "Evaluation", "Metric" ]	[ 0, 0, 0 ]
90	[ "All" ]	[ 0 ]
91	[ "the", "experiments", "were", "performed", "on", "a" ]	[ 0, 0, 0, 0, 0, 0 ]
92	[ "For", "the", "smallest", "three", "random", "seeds", "}", "dataset", "ARC-Challenge,", "we", "used", "five", "random", "seeds", "1,", "10,", "20,", "30,", "40", "}", "{" ]	[ 0, 0, 0, 0, 0, 0, 0, 0, 13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
93	[ "For", "CSQA,", "OBQA,", "ARC-Easy,", "and", "QASC,", "we", "used", "1,", "10,", "20", "." ]	[ 0, 13, 13, 13, 0, 13, 0, 0, 5, 5, 5, 0 ]
94	[ "Because", "neural", "models", "are", "known", "to", "be", "sensitive", "to", "different", "random", "seeds,", "especially", "when", "the", "training", "set", "is", "small,", "we", "performed", "multiple", "experiments", "for", "all", "models", "with", "different", "random", "seeds,", "and", "reported", "the", "mean", "and", "standard", "deviation." ]	[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]
95	[ "5" ]	[ 0 ]
96	[ "−" ]	[ 0 ]
97	[ "4,", "5e" ]	[ 5, 5 ]
98	[ "For", "each", "model,", "we", "searched", "for", "the", "best", "learning", "rate", "from", "1e", ",", "and", "for", "the", "best", "batch", "size", "{", "}", "−", "out", "of" ]	[ 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 5, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0 ]
99	[ "We", "used", "the", "Adam", "optimizer", "and", "set", "warmup", "fraction", "=", "0.1,", "weight", "decay", "=", "0.01,", "maximum", "source", "length", "=", "64,", "maximum", "target", "length", "=", "32,", "epoch", "=", "30,", "and", "early", "stop", "training", "when", "there", "was", "no", "better", "result", "on", "the", "dev", "set", "after", "5", "epochs." ]	[ 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 5, 3, 4, 0, 5, 3, 4, 4, 0, 5, 3, 4, 4, 0, 5, 3, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ]

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Dataset Card for [naacl2022]

Dataset Summary

This is a named entity recognition dataset annotated for the science entity recognition task, a project from the CMU 11-711 course.

Supported Tasks and Leaderboards

NER task.

Languages

English

Dataset Structure

Data Instances

A sample of the dataset {'id': '0', 'tokens': ['We', 'sample', '50', 'negative', 'cases', 'from', 'T5LARGE', '+', 'GenMC', 'for', 'each', 'dataset'], 'ner_tags':['O', 'O', 'O', 'O', 'O', 'O', 'B-MethodName', 'O', 'B-MethodName', 'O', 'O', 'O']}

Data Fields

id,tokens,ner_tags

id: a string feature give the sample index.
tokens: a list of string features give the sequence.
ner_tags: a list of classification labels for each token in the sentence, with possible values including O (0), B-MethodName (1), I-MethodName (2), B-HyperparameterName (3),I-HyperparameterName (4),B-HyperparameterValue (5),I-HyperparameterValue (6),B-MetricName (7),I-MetricName (8),B-MetricValue (9),I-MetricValue (10),B-TaskName (11),I-TaskName (12),B-DatasetName (13),I-DatasetName (14).