We compare two ways of obtaining lexical knowledge for antecedent selection in other-anaphora
and definite noun phrase coreference. Specifically, we compare an algorithm that relies on links
encoded in the manually created lexical hierarchy WordNet and an algorithm that mines corpora
by means of shallow lexico-semantic patterns. As corpora we use the British National
Corpus (BNC), as well as the Web, which has not been previously used for this task. Our
results show that (a) the knowledge encoded in WordNet is often insufficient, especially for
anaphor-antecedent relations that exploit subjective or context-dependent knowledge; (b) for
other-anaphora, the Web-based method outperforms the WordNet-based method; (c) for definite
NP coreference, the Web-based method yields results comparable to those obtained using
WordNet over the whole dataset and outperforms the WordNet-based method on subsets of the
dataset; (d) in both case studies, the BNC-based method is worse than the other methods because
of data sparseness. Thus, in our studies, the Web-based method alleviated the lexical knowledge
gap often encountered in anaphora resolution, and handled examples with context-dependent relations
between anaphor and antecedent. Because it is inexpensive and needs no hand-modelling
of lexical knowledge, it is a promising knowledge source to integrate in anaphora resolution systems