EntityPro annotates named entities, i.e. proper names of persons,
locations and organizations, in a text. The module is based on a
statistical classifier and makes use of local features, gazetteers, long-distance features and
distributional features extracted from very large non-annotated corpora.
To allow for easy domain adaptation, EntityPro implements white
and black lists, through which you can force a specific behavior of the
classifier on certain entities. The module is available with pre-trained models in the news domain for three languages, and has been integrated into the TextPro Active Learning platform. Example  Algorithm: EntityPro uses Yamcha for feature extraction and SVM as a classification algorithm. Reference: Emanuele Pianta and Roberto Zanoli. EntityPro: Exploiting SVM for Italian Named Entity Recognition. Intelligenza Artificiale – numero speciale su Strumenti per l’elaborazione del linguaggio naturale per l’italiano EVALITA 2007, vol. 4, no. 2, pp. 69-70, Associazione Italiana per l’Intelligenza Artificiale, 2007. |
Modules >