Papers with DialogRE
GRASP: Guiding Model with RelAtional Semantics Using Prompt for Dialogue Relation Extraction (2022.coling-1)
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| Challenge: | Existing studies utilize pre-trained language models with extensive features to supplement the low information density of the dialogue by multiple speakers. |
| Approach: | They propose a dialogue-based relation extraction task that leverages pre-trained language models to capture relational semantic clues of a given dialogue using an argument-aware prompt marker strategy and a relational clue detection task. |
| Outcome: | The proposed model achieves state-of-the-art on a DialogRE dataset even though it only leverages pre-trained language models without adding any extra layers. |
SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues (2021.acl-long)
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| Challenge: | Existing studies focus on identifying entities' relations from the semantics of dialogues-they utilize either the attention mechanism or a refined token graph to locate informative words. |
| Approach: | They propose a sequential structure prediction task to incrementally parse SocAoG for dynamic inference upon any incoming utterance. |
| Outcome: | Empirical results show that the proposed model infers social relations more accurately than the state-of-the-art methods. |
The CRECIL Corpus: a New Dataset for Extraction of Relations between Characters in Chinese Multi-party Dialogues (2022.lrec-1)
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Yuru Jiang, Yang Xu, Yuhang Zhan, Weikai He, Yilin Wang, Zixuan Xi, Meiyun Wang, Xinyu Li, Yu Li, Yanchao Yu
| Challenge: | Existing datasets focus on relation extraction between two entities in one sentence, and some focus on cross-sentence relationships. |
| Approach: | They propose to use a Chinese multi-party dialogue dataset for automatic extraction of dialogue-based character relationships. |
| Outcome: | The proposed dataset extracts relationships between 140 entities on the CRECIL corpus and another existing relation extraction corpus. |
Dialogue-Based Relation Extraction (2020.acl-main)
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| Challenge: | Existing dialogue-based relation extraction tasks focus on texts from formal genres such as professionally written and edited news reports or well-edited websites. |
| Approach: | They propose to use DialogRE to study cross-sentence relation extraction . they propose to annotate 36 possible relation types between arguments in dialogues . |
| Outcome: | The proposed dataset supports the prediction of relation(s) between two arguments that appear in a dialogue. |