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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Sources
- 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 ↗
How to cite this page
ScholarGate. (2026, June 22). Part-of-Speech Tagging in Corpus and Computational Linguistics. ScholarGate. https://scholargate.app/en/linguistics/part-of-speech-tagging
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Collocation AnalysisText mining↔ compare
- Corpus Concordance AnalysisLinguistics↔ compare
- Multidimensional Register AnalysisLinguistics↔ compare
- N-gram AnalysisLinguistics↔ compare