mlsanityData to 7 Oct 2026

Multilingual Coreference Resolution in Multiparty Dialogue

arXiv 2208.01307 ↗First posted 2 Aug 2022cs.CL cs.AIcited by 2

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Abstract (arXiv)

Existing multiparty dialogue datasets for entity coreference resolution are nascent, and many challenges are still unaddressed. We create a large-scale dataset, Multilingual Multiparty Coref (MMC), for this task based on TV transcripts. Due to the availability of gold-quality subtitles in multiple languages, we propose reusing the annotations to create silver coreference resolution data in other languages (Chinese and Farsi) via annotation projection. On the gold (English) data, off-the-shelf models perform relatively poorly on MMC, suggesting that MMC has broader coverage of multiparty coreference than prior datasets. On the silver data, we find success both using it for data augmentation and training from scratch, which effectively simulates the zero-shot cross-lingual setting.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 35 of its 88 references that are in the map. First posted on arXiv 2 Aug 2022.

Builds on

35 of 88 references.

References · 35

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23 more
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Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2023Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspectivecited by 6
  2. 2024Context-Aware Machine Translation with Source Coreference Explanationcited by 2