Abstract
This paper describes a knowledge-poor anaphora resolution approach based on a shallow meaning representation of sentences. The structure afforded in such a representation provides immediate identification of local domains which are required for resolving pronominal anaphora. Other kinds of information used include syntactic information, structure parallelism and salience weights. We collected 111 singular 3rd person pronouns from open domain resources such as children’s novel and examples from several anaphora resolution papers. There are 111 third-person singular pronouns in the experiment data set and 94 of them demonstrate pronominal anaphora in domain of test data. The system successfully resolves 78.4% of anaphoric examples.
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Ho, H., Min, K., Yeap, W.K. (2004). Pronominal Anaphora Resolution Using a Shallow Meaning Representation of Sentences. In: Zhang, C., W. Guesgen, H., Yeap, WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science(), vol 3157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28633-2_91
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DOI: https://doi.org/10.1007/978-3-540-28633-2_91
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