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EnglishWe investigate two publicly available web knowledge bases, Wikipedia and Yago, in an attempt to leverage semantic information and increase the performance level of a state-of-the-art coreference resolution (CR) engine. We extract semantic compatibility and aliasing information from Wikipedia and Yago, and incorporate it into a CR system. We show that using such knowledge with no disambiguation and filtering does not bring any improvement over the baseline, mirroring the previous findings (Ponzetto and Poesio 2009). We propose, therefore, a number of solutions to reduce the amount of noise coming from web resources: using disambiguation tools for Wikipedia, pruning Yago to eliminate the most generic categories and imposing additional constraints on affected mentions. Our evaluation experiments on the ACE-02 corpus show that the knowledge, extracted from Wikipedia and Yago, improves our system's performance by 2-3 percentage points.
| Titolo: | Disambiguation and filtering methods in using web knowledge for coreference resolution | |
| Autori: | Uryupina, Olga; Poesio, Massimo; C., Giuliano; Tymoshenko, Kateryna | |
| Autori Unitn: | ||
| Titolo del volume contenente il saggio: | Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence | |
| Luogo di edizione: | Palo Alto, CA, USA | |
| Casa editrice: | American Association for Artificial Intelligence (AAAI) | |
| Anno di pubblicazione: | 2011 | |
| Codice identificativo Scopus: | 2-s2.0-80052403950 | |
| ISBN: | 9781577355014 | |
| Handle: | http://hdl.handle.net/11572/89837 | |
| Appare nelle tipologie: | 04.1 Saggio in atti di convegno (Paper in proceedings) |
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