HFST-SweNER — A New NER Resource for Swedish

Dimitrios Kokkinakis, Jyrki Niemi, Sam Hardwick, Krister Lindén, Lars Borin

Abstract
Named entity recognition (NER) is a knowledge-intensive information extraction task that is used for recognizing textual mentions of entities that belong to a predefined set of categories, such as locations, organizations and time expressions. NER is a challenging, difficult, yet essential preprocessing technology for many natural language processing applications, and particularly crucial for language understanding. NER has been actively explored in academia and in industry especially during the last years due to the advent of social media data. This paper describes the conversion, modeling and adaptation of a Swedish NER system from a hybrid environment, with integrated functionality from various processing components, to the Helsinki Finite-State Transducer Technology (HFST) platform. This new HFST-based NER (HFST-SweNER) is a full-fledged open source implementation that supports a variety of generic named entity types and consists of multiple, reusable resource layers, e.g., various n-gram-based named entity lists (gazetteers).
Anthology ID:
L14-1339
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2537–2543
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/391_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Dimitrios Kokkinakis, Jyrki Niemi, Sam Hardwick, Krister Lindén, and Lars Borin. 2014. HFST-SweNER — A New NER Resource for Swedish. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2537–2543, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
HFST-SweNER — A New NER Resource for Swedish (Kokkinakis et al., LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/391_Paper.pdf
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