XCoref: Cross-document Coreference Resolution in the Wild

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SMITS, Malte, ed.. Information for a better world: shaping the global future : 17th international conference, iConference 2022, virtual event, February 28 - March 4, 2022 : proceedings, part 1. Cham: Springer Nature, 2022, pp. 272-291. Lecture Notes in Computer Science. 13192. ISBN 978-3-030-96956-1. Available under: doi: 10.1007/978-3-030-96957-8_25
Zusammenfassung

Datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities with strict coreference relations. They lack, however, annotating and resolving coreference mentions with more abstract or loose relations that may occur when news articles report about controversial and polarized events. Bridging and loose coreference relations trigger associations that may expose news readers to bias by word choice and labeling. For example, coreferential mentions of “direct talks between U.S. President Donald Trump and Kim” such as “an extraordinary meeting following months of heated rhetoric” or “great chance to solve a world problem” form a more positive perception of this event. A step towards bringing awareness of bias by word choice and labeling is the reliable resolution of coreferences with high lexical diversity. We propose an unsupervised method named XCoref, which is a CDCR method that capably resolves not only previously prevalent entities, such as persons, e.g., “Donald Trump,” but also abstractly defined concepts, such as groups of persons, “caravan of immigrants,” events and actions, e.g., “marching to the U.S. border.” In an extensive evaluation, we compare the proposed XCoref to a state-of-the-art CDCR method and a previous method TCA that resolves such complex coreference relations and find that XCoref outperforms these methods. Outperforming an established CDCR model shows that the new CDCR models need to be evaluated on semantically complex mentions with more loose coreference relations to indicate their applicability of models to resolve mentions in the “wild” of political news articles.

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004 Informatik
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iConference 2022 : Information for a Better World: shaping the global future, 28. Feb. 2022 - 4. März 2022, Virtual Event
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ISO 690ZHUKOVA, Anastasia, Felix HAMBORG, Karsten DONNAY, Bela GIPP, 2022. XCoref: Cross-document Coreference Resolution in the Wild. iConference 2022 : Information for a Better World: shaping the global future. Virtual Event, 28. Feb. 2022 - 4. März 2022. In: SMITS, Malte, ed.. Information for a better world: shaping the global future : 17th international conference, iConference 2022, virtual event, February 28 - March 4, 2022 : proceedings, part 1. Cham: Springer Nature, 2022, pp. 272-291. Lecture Notes in Computer Science. 13192. ISBN 978-3-030-96956-1. Available under: doi: 10.1007/978-3-030-96957-8_25
BibTex
@inproceedings{Zhukova2022XCore-57335,
  year={2022},
  doi={10.1007/978-3-030-96957-8_25},
  title={XCoref: Cross-document Coreference Resolution in the Wild},
  number={13192},
  isbn={978-3-030-96956-1},
  publisher={Springer Nature},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={Information for a better world: shaping the global future : 17th international conference, iConference 2022, virtual event, February 28 - March 4, 2022 : proceedings, part 1},
  pages={272--291},
  editor={Smits, Malte},
  author={Zhukova, Anastasia and Hamborg, Felix and Donnay, Karsten and Gipp, Bela}
}
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