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.
Izvorni zapis
Citati kopirani doslovno iz izvornog zapisa metode. Ne impliciraju nikakvu provjeru na razini tvrdnje.
- 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
Uređene tvrdnje
Tvrdnje pohranjene u knjigu dokaza, svaka s vlastitom procjenom.
Ovaj prikaz ne izmišlja procjenu tvrdnje kada knjiga dokaza nema nijednu.
Povezane metode
Generirano iz grafa metode i prikazano kao strojno predložene relacije — ne implicira se nikakva tvrdnja dokaza.