Optimizing Differentiable Relaxations of Coreference Evaluation Metrics
Table 2: Number of: “false anaphor” (FA, a non-anaphoric mention marked as anaphoric), “false new” (FN, an anaphoric mention marked as non-anaphoric), and “wrong link” (WL, an anaphoric mention is linked to a wrong antecedent) errors on the development set.
['[EMPTY]', 'Non-Anaphoric (FA) Proper', 'Non-Anaphoric (FA) Nominal', 'Non-Anaphoric (FA) Pronom.', 'Anaphoric (FN + WL) Proper', 'Anaphoric (FN + WL) Nominal', 'Anaphoric (FN + WL) Pronom.']
The proposed resolvers make fewer “false anaphor” and “wrong link” errors but more “false new” errors compared to the baseline. This suggests that loss optimization prevents over-clustering, driving the precision up: when antecedents are difficult to detect, the self-link (i.e., ai= i) is chosen. When β increases, they make more “false anaphor” and “wrong link” errors but less “false new” errors.