Part of Speech Tagging: Shallow or Deep Learning?
نویسندگان
چکیده
منابع مشابه
Shallow Parsing as Part-of-Speech Tagging
Treating shallow parsing as part-of-speech tagging yields results comparable with other, more elaborate approaches. Using the CoNLL 2000 training and testing material, our best model had an accuracy of 94.88%, with an overall FB1 score of 91.94%. The individual FB1 scores for NPs were 92.19%, VPs 92.70% and PPs 96.69%.
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This paper describes and evaluates shallow parsing of several Indian languages utilizing Conditional Random Field models. We show how performance can be substantially improved by several feature enhancements and improved modeling techniques, including expanding the chunk tag inventory, and separating punctuation from linguistic phrases. We also report results from part of speech tagging of Hind...
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We used four Part-of-Speech taggers, which are available for research purposes and were originally trained on text to tag a corpus of transcribed multiparty spoken dialogues. The assigned tags were then manually corrected. The correction was first used to evaluate the four taggers, then to retrain them. Despite limited resources in time, money and annotators we reached results comparable to tho...
متن کاملUnsupervised Learning of Disambiguation Rules for Part of Speech Tagging
In this paper we describe an unsupervised learning algorithm for automatically training a rule-based part of speech tagger without using a manually tagged corpus. We compare this algorithm to the Baum-Welch algorithm, used for unsupervised training of stochastic taggers. Next, we show a method for combining unsupervised and supervised rule-based training algorithms to create a highly accurate t...
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ژورنال
عنوان ژورنال: Northern European Journal of Language Technology
سال: 2018
ISSN: 2000-1533
DOI: 10.3384/nejlt.2000-1533.1851