H. Burcu Kupelioglu, Tankut Acarman, Bernard Levrat, Tassadit Amghar
Metonymy, Named Entity, Natural Language Processing, WordNet, Stanford CoreNLP, Dependency Parsing, Figurative Speech, Lesk Algorithm
Metonymy resolution approaches mainly use semantic classifiers, discourse understanding, annotated names lists or unsupervised methods. In our work we propose to expand those approaches that most of the metonymies are caused by a named entity and especially a verb connected with it. Though a well prepared thesaurus and a natural language processing toolkit will be enough for metonymy resolution. The named entity recognition tools are more developed then before therefore use of them for metonymy recognition will help to eliminate human work.
Cite this paper
H. Burcu Kupelioglu, Tankut Acarman, Bernard Levrat, Tassadit Amghar. (2016) Helping Metonymy Recognition and Treatment through Named Entity Recognition. International Journal of Education and Learning Systems, 1, 118-123