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Syntactic Multi-view Learning for Open Information Extraction
Kuicai Dong, Aixin Sun, Jung-Jae Kim +1
Open Information Extraction (OpenIE) aims to extract relational tuples from open-domain sentences. Traditional rule-based or statistical models have been developed based on syntact…
Perplexity from PLM Is Unreliable for Evaluating Text Quality
Yequan Wang, Jiawen Deng, Aixin Sun +1
Recently, amounts of works utilize perplexity~(PPL) to evaluate the quality of the generated text. They suppose that if the value of PPL is smaller, the quality(i.e. fluency) of th…
CofeNet: Context and Former-Label Enhanced Net for Complicated Quotation Extraction
Yequan Wang, Xiang Li, Aixin Sun +3
Quotation extraction aims to extract quotations from written text. There are three components in a quotation: source refers to the holder of the quotation, cue is the trigger word(…
A Survey on Neural Open Information Extraction: Current Status and Future Directions
Shaowen Zhou, Bowen Yu, Aixin Sun +5
Open Information Extraction (OpenIE) facilitates domain-independent discovery of relational facts from large corpora. The technique well suits many open-world natural language unde…
Chat-Capsule: A Hierarchical Capsule for Dialog-level Emotion Analysis
Yequan Wang, Xuying Meng, Yiyi Liu +4
Many studies on dialog emotion analysis focus on utterance-level emotion only. These models hence are not optimized for dialog-level emotion detection, i.e. to predict the emotion…
Aspect-based Sentiment Analysis through EDU-level Attentions
Ting Lin, Aixin Sun, Yequan Wang
A sentence may express sentiments on multiple aspects. When these aspects are associated with different sentiment polarities, a model's accuracy is often adversely affected. We obs…