Rezumat articol ediţie STUDIA UNIVERSITATIS BABEŞ-BOLYAI

În partea de jos este prezentat rezumatul articolului selectat. Pentru revenire la cuprinsul ediţiei din care face parte acest articol, se accesează linkul din titlu. Pentru vizualizarea tuturor articolelor din arhivă la care este autor/coautor unul din autorii de mai jos, se accesează linkul din numele autorului.

INTRODUCTION. In the last few years, Wikipedia has become a very useful resource for NLP offering access to both structured and unstructured information that can be used for further language processing. One particularity of the Wikipedia articles is that they focus on only one topic (e.g. a product, person, location or event), which is detailed throughout the article. In order to extract comprehensive information from these articles, it is necessary to be able to track different expressions that refer to the topic. This paper discusses the issues to be tackled when a topic tracking algorithm is implemented. In order to address this problem, a shallow rule-based coreference resolution method for topic tracking was implemented.

Key words and phrases. coreference resolution, Wikipedia, near identity.