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