CoreNet is a lexico-semantic network of 73,100 Korean word senses, which are categorized under 2,937 semantic categories organized in a taxonomy. Recently, to foster the more widespread use of CoreNet, there was an attempt to map the semantic categories of CoreNet into synsets of Princeton WordNet by lexical relations such as synonymy, hyponymy, and hypernymy relations. One of the limitations of the existing mapping is that it is only focused on mapping the semantic categories, but not on mapping the word senses, which are the majority part (96%) of CoreNet. To boost bridging the gap between CoreNet and WordNet, we introduce the automatic mapping approach to link the word senses of CoreNet into WordNet synsets. The evaluation shows that our approach successfully maps previously unmapped 38,028 word senses into WordNet synsets with the precision of 91.2% (±1.14 with 99% confidence).
@InProceedings{KIM18.892, author = {Jiseong Kim and Younggyun Hahm and Sunggoo Kwon and KEY-SUN CHOI}, title = "{Automatic Wordnet Mapping: from CoreNet to Princeton WordNet}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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