Summary of the paper

Title Evaluating the Impact of Phrase Recognition on Concept Tagging
Authors Pablo Mendes, Joachim Daiber, Rohana Rajapakse, Felix Sasaki and 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.
Topics Information Extraction, Information Retrieval, Named Entity recognition, Word Sense Disambiguation
Full paper Evaluating the Impact of Phrase Recognition on Concept Tagging
Bibtex @InProceedings{MENDES12.545,
  author = {Pablo Mendes and Joachim Daiber and Rohana Rajapakse and Felix Sasaki and Christian Bizer},
  title = {Evaluating the Impact of Phrase Recognition on Concept Tagging},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
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