2017
EACL
EACL 2017
Morphological Analysis without Expert Annotation
Abstract
AbstractThe task of morphological analysis is to produce a complete list of lemma+tag analyses for a given word-form. We propose a discriminative string transduction approach which exploits plain inflection tables and raw text corpora, thus obviating the need for expert annotation. Experiments on four languages demonstrate that our system has much higher coverage than a hand-engineered FST analyzer, and is more accurate than a state-of-the-art morphological tagger.
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Interdisciplinary Bridge
— Interdisciplinary and Machine Learning and Natural Language Processing
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Keyword Pioneer
— string transduction
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Hot Topic Early Bird
— morphological analysis
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
Authors
Topics
Machine Learning > Core Methods > Classification
Natural Language Processing > Applications > Text Classification
Interdisciplinary > Linguistics > Computational Linguistics
Interdisciplinary > Linguistics > Morphology
Machine Learning > Core Methods > Feature Learning
Natural Language Processing > Understanding > Morphology