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index | dataset | Abbreviation | task | note |
---|---|---|---|---|
1 | LiBriSpeech | Automatic speech recogniton | ||
2 | WSJ | Automatic speech recogniton | ||
3 | Hub5’00 Evaluation | Automatic speech recogniton | ||
4 | Rich Transcriptions | Automatic speech recogniton | ||
5 | Fisher | RT03S FSH | Automatic speech recogniton | |
6 | TED-LIUM | Automatic speech recogniton | ||
7 | CHiME | CHiME | Automatic speech recogniton | noisy speech |
8 | TIMIT | Automatic speech recogniton | ||
9 | CCGBank | CCG supertagging | ||
10 | Event2Mind | Common sense | ||
11 | Situations with Adversarial Generations | SWAG | Common sense | |
12 | Winograd Schema Challenge | Common sense | ||
13 | Visual Commonsense Reasoning | VCR | Common sense | |
14 | Penn Treebank | Constituency parsing | ||
15 | CoNLL 2012 | Coreference resolution | ||
16 | Penn Treebank | Dependency parsing | ||
17 | Penn Treebank | Unsupervised dependency parsing | ||
18 | Switchboard corpus | Dialogue | Dialogue act classification | |
19 | Switchboard Dialogue Act Corpus | SwDA | Dialogue | Dialogue act classification |
20 | ICSI Meeting Recorder Dialog Act corpus | MRDA | Dialogue | Dialogue act classification |
21 | Second dialogue state tracking challenge | DSTC2 | Dialogue | Dialogue state tracking |
22 | Wizard-of-Oz | Dialogue | Dialogue state tracking | |
23 | Ubuntu Corpus | Dialogue | Retrieval-based Chatbot | |
24 | Multi-Domain Sentiment Dataset | Domain adaptation | Sentiment analysis | |
25 | AIDA CoNLL-YAGO Dataset | Entity Linking | ||
26 | TAC KBP English Entity Linking Comprehensive and Evaluation Data 2010 | Entity Linking | ||
27 | CoNLL-2014 Shared Task | Grammatical Error Correction | ||
28 | CoNLL-2014 10 Annotations | Grammatical Error Correction | ||
29 | JFLEG | Grammatical Error Correction | ||
30 | Base | Information Extraction | Open Knowledge Graph Canonicalization | |
31 | Ambigous | Information Extraction | Open Knowledge Graph Canonicalization | |
32 | ReVerb45K | Information Extraction | Open Knowledge Graph Canonicalization | |
33 | Penn Treebank | Language modeling | Word Level Models | |
34 | WikiText-2 | Language modeling | Word Level Models | |
35 | WikiText-103 | Language modeling | Word Level Models | |
36 | 1B Words / Google Billion Word benchmark | Language modeling | Word Level Models | |
37 | Hutter Prize | Language modeling | Character Level Models | |
38 | Text8 | Language modeling | Character Level Models | |
39 | Penn Treebank | Language modeling | Character Level Models | |
40 | LexNorm | Lexical Normalization | ||
41 | LexNorm2015 | Lexical Normalization | ||
42 | WMT 2014 EN-DE | Machine translation | ||
43 | WMT 2014 EN-FR | Machine translation | ||
44 | DecalNLP | Multi-task learning | ||
45 | GLUE | Multi-task learning | ||
46 | IEMOCAP | Multimodal | Multimodal Emotion Recognition | |
47 | Multimodal | Multimodal Metaphor Recognition | ||
48 | MOSI | Multimodal | Multimodal Sentiment Analysis | |
49 | CoNLL 2003(English) | Named entity recognition | ||
50 | Long-tail emerging entities | Named entity recognition | ||
51 | Ontonotes v5 | Named entity recognition | ||
52 | Stanford Natural Language Inference Corpus | SNLI | Natural language inference | |
53 | Multi-Genre Natural Langeuage Inference corpus | MultiNLI | Natural language inference | |
54 | SciTail | Natural language inference | ||
55 | Penn Treebank | Part-of-speech tagging | ||
56 | Social media | Part-of-speech tagging | ||
57 | Universal Dependencies | Part-of-speech tagging | ||
58 | AI2 Reasoning Challenge | ARC | Question answering | |
59 | ShARC | ShARC | Question answering | |
60 | CLiCR | CLiCR | Question answering | Reading comprehension |
61 | CNN/Daily Mail | Question answering | Reading comprehension | |
62 | CoQA | Question answering | Reading comprehension | |
63 | HotpotQA | Question answering | Reading comprehension | |
64 | MS MARCO | Question answering | Reading comprehension | |
65 | MultiRC | Question answering | Reading comprehension | |
66 | NewsQA | Question answering | Reading comprehension | |
67 | QAngaroo | Question answering | Reading comprehension | |
68 | QuAC | Question answering | Reading comprehension | |
69 | RACE | Question answering | Reading comprehension | |
70 | Stanford Question Answering Dataset | SQuAD | Question answering | Reading comprehension |
71 | Story Cloze Test | Question answering | Reading comprehension | |
72 | RecipeQA | Question answering | Reading comprehension | |
73 | NarrativeQA | Question answering | Reading comprehension | |
74 | DuoRC | Question answering | Reading comprehension | |
75 | DuReader | Question answering | Open-domain Question Answering | |
76 | Quasar | Question answering | Open-domain Question Answering | |
77 | SearchQA | Question answering | Open-domain Question Answering | |
78 | Freebase-15K-238 | FB15K-237 | Relation Prediction | |
79 | WordNet-18-RR | WN18RR | Relation Prediction | |
80 | New York Times Corpus | Relationship Extraction | ||
81 | SemEval-2010 Task 8 | Relationship Extraction | ||
82 | TACRED | TACRED | Relationship Extraction | |
83 | Few-Shot Relation Classification Dataset | FewRel | Relationship Extraction | |
84 | SentEval | Semantic textual similarity | ||
85 | Quora Question Pairs | Semantic textual similarity | Paraphrase identification | |
86 | LDC2014T12 | Semantic parsing | AMR parsing | |
87 | LDC2015E86 | Semantic parsing | AMR parsing | |
88 | LDC2016E25 | Semantic parsing | AMR parsing | |
89 | ATIS | Semantic parsing | SQL parsing | |
90 | Advising | Semantic parsing | SQL parsing | |
91 | GeoQuery | Semantic parsing | SQL parsing | |
92 | Scholar | Semantic parsing | SQL parsing | |
93 | Spider | Semantic parsing | SQL parsing | |
94 | WikiSQL | Semantic parsing | SQL parsing | |
95 | Smaller Datasets | Semantic parsing | SQL parsing | |
96 | OntoNotes | Semantic role labeling | ||
97 | IMDb | Sentiment analysis | ||
98 | Stanford Sentiment Treebank | SST | Sentiment analysis | |
99 | Yelp Review dataset | Yelp | Sentiment analysis | |
100 | SemEval | Sentiment analysis | ||
101 | Sentihood | Sentiment analysis | Aspect-based sentiment analysis | |
102 | SemEval-2014 Task 4 | Sentiment analysis | Aspect-based sentiment analysis | |
103 | Subjectivity dataset | SUBJ | Sentiment analysis | Subjectivity analysis |
104 | Penn Treebank | Shallow syntax | Chunking | |
105 | Main-Simple English Wikipedia | Simplification | Sentence Simplification | |
106 | PWKP/WikiSmall | Simplification | Sentence Simplification | |
107 | Coster and Kauchack | Simplification | Sentence Simplification | |
108 | Turk Corpus | Simplification | Sentence Simplification | |
108 | Newsela | Simplification | Sentence Simplification | |
109 | RumourEval | Stance detection | ||
110 | CNN/Daily Mail | Summarization | ||
110 | Gigaword | Summarization | ||
111 | DUC 2004 Task 1 | Summarization | ||
112 | Webis-TLDR-17 Corpus | Summarization | ||
113 | Google Dataset | Summarization | Sentence Compression | |
114 | SemEval 2018 | Taxonomy Learning | Hypernym Discory | |
115 | APW | Temporal Processing | Document Dating(Time-stamping) | |
116 | NYT | Temporal Processing | Document Dating(Time-stamping) | |
117 | TimeBank | Temporal Processing | Temporal Information Extraction | |
118 | TempEval-3 | Temporal Processing | Temporal Information Extraction | |
119 | TimeBank | Temporal Processing | Timex normalisation | |
120 | PNT | Temporal Processing | Timex normalisation | |
121 | AG News corpus | Text classification | ||
122 | DBpedia | Text classification | ||
123 | TREC | Text classification | ||
124 | Fine-grained WSD | Word Sense Disambiguation | ||
125 | AIDA CoNLL-YAGO Dataset | Entity linking | ||
126 | Chinese Treebank 6 | Chinese Word Segmentation | ||
127 | Chinese Treebank 7 | Chinese Word Segmentation | ||
128 | AS | Chinese Word Segmentation | ||
129 | CityU | Chinese Word Segmentation | ||
130 | PKU | Chinese Word Segmentation | ||
131 | MSR | Chinese Word Segmentation |
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