FinnPos: an open-source morphological tagging and lemmatization toolkit for Finnish.
This paper describes FinnPos, an open-source morphological tagging and lemmatization toolkit for Finnish. The morphological tagging model is based on the averaged structured perceptron classifier. Given training data, new taggers are estimated in a computationally efficient manner using a combinatio...
| Published in: | Language Resources & Evaluation Vol. 50; no. 4; pp. 863 - 879 |
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| Main Authors: | , , , |
| Format: | Article |
| Published: |
Springer Nature
Dec2016
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=119384311&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 119384311 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 1574020X 179V jtl: Language Resources & Evaluation issn: 1574020X maglogo: N pubinfo: dt: Dec2016 vid: 50 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 119384311 10.1007/s10579-015-9326-3 ppf: 863 ppct: 16 formats: fmt: @attributes: type: P size: 412KB tig: atl: FinnPos: an open-source morphological tagging and lemmatization toolkit for Finnish. aug: au: Silfverberg, Miikka Ruokolainen, Teemu Lindén, Krister Kurimo, Mikko affil: University of Helsinki , Helsinki Finland Aalto University , Helsinki Finland su: Open source software Linguistic analysis Vocabulary Perceptrons Artificial intelligence sug: subj: Open source software Linguistic analysis Vocabulary Perceptrons Artificial intelligence keyword: Averaged perceptron Data-driven lemmatization Finnish Morphological tagging Open-source ab: This paper describes FinnPos, an open-source morphological tagging and lemmatization toolkit for Finnish. The morphological tagging model is based on the averaged structured perceptron classifier. Given training data, new taggers are estimated in a computationally efficient manner using a combination of beam search and model cascade. The lemmatization is performed employing a combination of a rule-based morphological analyzer, OMorFi, and a data-driven lemmatization model. The toolkit is readily applicable for tagging and lemmatization of running text with models learned from the recently published Finnish Turku Dependency Treebank and FinnTreeBank. Empirical evaluation on these corpora shows that FinnPos performs favorably compared to reference systems in terms of tagging and lemmatization accuracy. In addition, we demonstrate that our system is highly competitive with regard to computational efficiency of learning new models and assigning analyses to novel sentences. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Language Resources & Evaluation is a copyright of Springer, 2016. All Rights Reserved. item: Language Resources & Evaluation holder: Springer Nature dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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