Anaphora Resolution in Dialogue: System Description (CODI-CRAC 2022 Shared Task)
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Abstract (arXiv)
We describe three models submitted for the CODI-CRAC 2022 shared task. To perform identity anaphora resolution, we test several combinations of the incremental clustering approach based on the Workspace Coreference System (WCS) with other coreference models. The best result is achieved by adding the ''cluster merging'' version of the coref-hoi model, which brings up to 10.33% improvement 1 over vanilla WCS clustering. Discourse deixis resolution is implemented as multi-task learning: we combine the learning objective of corefhoi with anaphor type classification. We adapt the higher-order resolution model introduced in Joshi et al. (2019) for bridging resolution given gold mentions and anaphors.
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References · 8
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- 2020MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformerscited by 1,463
- 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,067
- 2018Higher-order Coreference Resolution with Coarse-to-fine Inferencecited by 150
- 2019BERT for Coreference Resolution: Baselines and Analysiscited by 125
- 2018Multilingual Constituency Parsing with Self-Attention and Pre-Trainingcited by 117
- 2020Revealing the Myth of Higher-Order Inference in Coreference Resolutioncited by 49
- 2021Adapted End-to-End Coreference Resolution System for Anaphoric Identities in Dialoguescited by 5
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