Adapting word2vec to Named Entity Recognition
- Titel
- Adapting word2vec to Named Entity Recognition
- Urheber
- Scharolta Katharina Sienčnik
- Zusammenfassung
- In this paper we explore how word vectors built using word2vec can be used to improve the performance of a classifier during Named Entity Recognition. Thereby, we discuss the best integration of word embeddings into the classification problem and consider the effect of the size of the unlabelled dataset on performance, reaching the unexpected result that for this particular task increasing the amount of unlabelled data does not necessarily increase the performance of the classifier.
- Datum
- 2015
- Ist Teil von
- Adapting word2vec to Named Entity Recognition
- presented at
- Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania
- Verleger
- Link�ping University Electronic Press, Link�pings universitet
- Seiten
- 239-243
- isbn
- 1650-3740
- Sammlungen
- Zotero