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Source Entity Source Type Relationship Target Entity Type Paper ID
Hybrid Models method achieves SOTA Accuracy metric 30644.0
Hybrid Models method comparesWith Distributional Models method 26156.0
Hybrid Models method comparesWith Knowledge Based Models method 26156.0
Hybrid Models method comparesWith Linguistic Models method 28401.0
Hybrid Models method comparesWith Neural Models method 28401.0
Hybrid Models method evaluatedIn ChineseDataset material 28401.0
Hybrid Models method evaluatedIn Lexical Similarity metric 26156.0
Hybrid Models method evaluatedIn Word Sense Disambiguation task 26156.0
Hybrid Models method improves Classification Accuracy metric 30644.0
Hybrid Models method uses Attention Mechanism method 40536.0
Hybrid Models method uses WordNet material 26156.0
Hybrid Morpheme Word Representation method extends Joint Scoring method 44618.0
Hybrid Morpheme Word Representation method extends Minimum Error Rate Training method 44618.0
Hybrid NLP System material improves Natural Language Processing otherentity 1139.0
Hybrid Neural Model method proposedFor Grammatical Error Correction task 40044.0
Hybrid Neural Model method uses Nested Attention Mechanism method 40044.0
Hybrid Neural Network method appliesTo Attention Model method 14092.0
Hybrid Neural Network method combines Bidirectional Language Model method 14092.0
Hybrid Neural Network method combines Long Short Term Memory method 14092.0
Hybrid Neural Network method evaluates Leave One Out Cross Validation method 14092.0