An algorithm for pronominal anaphora resolution
Computational Linguistics
Automatic processing of large corpora for the resolution of anaphora references
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
Probabilistic reasoning for entity & relation recognition
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Improving the identification of non-anaphoric it using support vector machines
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Bayesian information extraction network
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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The NLP systems often have low performances because they rely on unreliable and heterogeneous knowledge. We show on the task of non-anaphoric it identification how to overcome these handicaps with the Bayesian Network (BN) formalism. The first results are very encouraging compared with the state-of-the-art systems.