Part-of-Speech Tagging
Part-of-speech (POS) tagging is the task of assigning each word (token) in a text its grammatical category — noun, verb, adjective, preposition, and finer distinctions such as past-tense verb or comparative adjective — drawn from a fixed tagset. Because the same word form can belong to different categories depending on context ("book a flight" versus "read a book"), tagging is fundamentally a disambiguation problem solved with contextual evidence. It is one of the oldest and most foundational tasks in natural language processing and corpus linguistics, supplying the grammatical layer on which concordancing, parsing, register analysis, and information extraction all depend. Modern taggers reach accuracies well above 97% on standard English benchmarks, using statistical sequence models or neural networks trained on annotated corpora.
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来源
- Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to Information Retrieval. Cambridge University Press. ISBN: 9780521865715
- Jurafsky, D., & Martin, J. H. (2023). Speech and Language Processing (3rd ed. draft). Stanford University. link ↗
- Marcus, M. P., Marcinkiewicz, M. A., & Santorini, B. (1993). Building a large annotated corpus of English: The Penn Treebank. Computational Linguistics, 19(2), 313–330. link ↗
如何引用本页
ScholarGate. (2026, June 22). Part-of-Speech Tagging in Corpus and Computational Linguistics. ScholarGate. https://scholargate.app/zh/linguistics/part-of-speech-tagging
选用哪种方法?
将本方法与其最相近的同类并置,并排研读——本馆将书籍铺陈于案上,取舍则由您定夺。
- 搭配分析文本挖掘↔ 比较
- Corpus Concordance Analysis语言学↔ 比较
- Multidimensional Register Analysis语言学↔ 比较
- N-gram Analysis语言学↔ 比较