We present a probabilistic framework for inferring coreference relations among person names in a news collection. The approach does not assume any prior knowledge about persons (e.g. an ontology) mentioned in the collection and requires basic linguistic processing (named entity recognition) and resources (a dictionary of person names). The system parameters have been estimated on a 5K corpus of Italian news documents. Evaluation, over a sample of four days news documents, shows that the error rate of the system (1.4%) is above a baseline (5.4%) for the task. Finally, we discuss alternative approaches for evaluation. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Popescu, O., & Magnini, B. (2007). Inferring coreferences among person names in a large corpus of news collections. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4733 LNAI, pp. 362–373). Springer Verlag. https://doi.org/10.1007/978-3-540-74782-6_32
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