Evaluating the Impact of Phrase Recognition on Concept Tagging
Pablo Mendes, Joachim Daiber, Rohana Rajapakse, Felix Sasaki, Christian Bizer
Abstract
We have developed DBpedia Spotlight, a flexible concept tagging system that is able to annotate entities, topics and other terms in natural language text. The system starts by recognizing phrases to annotate in the input text, and subsequently disambiguates them to a reference knowledge base extracted from Wikipedia. In this paper we evaluate the impact of the phrase recognition step on the ability of the system to correctly reproduce the annotations of a gold standard in an unsupervised setting. We argue that a combination of techniques is needed, and we evaluate a number of alternatives according to an existing evaluation set.- Anthology ID:
- L12-1307
- Volume:
- Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)
- Month:
- May
- Year:
- 2012
- Address:
- Istanbul, Turkey
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 1277–1280
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/545_Paper.pdf
- DOI:
- Cite (ACL):
- Pablo Mendes, Joachim Daiber, Rohana Rajapakse, Felix Sasaki, and Christian Bizer. 2012. Evaluating the Impact of Phrase Recognition on Concept Tagging. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 1277–1280, Istanbul, Turkey. European Language Resources Association (ELRA).
- Cite (Informal):
- Evaluating the Impact of Phrase Recognition on Concept Tagging (Mendes et al., LREC 2012)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2012/pdf/545_Paper.pdf