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Algorithms for Scoring Coreference Chains

Summary

The paper proposes the B-cubed (B³) metric for evaluating coreference resolution. Instead of counting links between mentions, as the earlier MUC score does, B³ computes precision and recall for every individual mention: how much of the predicted cluster containing that mention overlaps with its gold cluster, and vice versa. The per-mention scores are then averaged, optionally with weights. This mention-centric view fixes known blind spots of link-based scoring, for example that merging everything into one large cluster is not punished enough and that singleton entities are ignored. B³ became one of the three components of the standard CoNLL coreference score, together with MUC and CEAF.

How Mova uses it

Effectiveness in Mova

This is an evaluation metric, not a modelling idea, so it has no gain of its own. It is the measuring instrument for all coreference results, e.g. the sieve resolver on GUM test with gold trees: CoNLL F1 73.04 with singletons (MUC / B³ / CEAF-e = 69.18 / 75.26 / 74.68), 60.31 without singletons (B³ 58.79), per the development notes of coref.


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Topics: Coreference resolution

Cite

The paper itself, not this card. BibTeX from the library's record of the work.

@inproceedings{bagga1998algorithms,
  title = {{Algorithms for Scoring Coreference Chains}},
  author = {Bagga, Amit and Baldwin, Breck},
  booktitle = {Proceedings of the LREC 1998 Workshop on Linguistic Coreference, Granada, 563–566},
  year = {1998}
}

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