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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
- 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. · URL
- 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. · URL
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相关方法
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