HFST-SweNER – A New NER Resource for Swedish

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

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

Abstrakti

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).
Alkuperäiskielienglanti
OtsikkoProceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
ToimittajatNicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Sivumäärä7
JulkaisupaikkaReykjavik, Iceland
KustantajaEuropean Language Resources Association (ELRA)
Julkaisupäivä26 toukokuuta 2014
Artikkeli no #391
ISBN (painettu)978-2-9517408-8-4
ISBN (elektroninen)978-2-9517408-8-4
TilaJulkaistu - 26 toukokuuta 2014
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaLanguage and Resource Evaluation Conference - Reykjavik, Islanti
Kesto: 26 toukokuuta 201431 toukokuuta 2014
Konferenssinumero: 9

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Siteeraa tätä

Kokkinakis, D., Niemi, J., Hardwick, S., Linden, K., & Borin, L. (2014). HFST-SweNER – A New NER Resource for Swedish. teoksessa N. Calzolari, K. Choukri, T. Declerck, H. Loftsson, B. Maegaard, J. Mariani, A. Moreno, J. Odijk, ... S. Piperidis (Toimittajat), Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14) [ #391] Reykjavik, Iceland: European Language Resources Association (ELRA).