Grammatical context is one way to determine this semantic analysis can also be used to infer that "sailor" and "hatch" implicate "dogs" as 1) in the nautical context and 2) an action applied to the object "hatch" (in this context, "dogs" is a nautical term meaning "fastens (a watertight door) securely"). For example, even "dogs", which is usually thought of as just a plural noun, can also be a verb:Ĭorrect grammatical tagging will reflect that "dogs" is here used as a verb, not as the more common plural noun. This is not rare-in natural languages (as opposed to many artificial languages), a large percentage of word-forms are ambiguous. Part-of-speech tagging is harder than just having a list of words and their parts of speech, because some words can represent more than one part of speech at different times, and because some parts of speech are complex or unspoken. Brill's tagger, one of the first and most widely used English POS-taggers, employs rule-based algorithms.
POS-tagging algorithms fall into two distinctive groups: rule-based and stochastic. Once performed by hand, POS tagging is now done in the context of computational linguistics, using algorithms which associate discrete terms, as well as hidden parts of speech, by a set of descriptive tags.
In corpus linguistics, part-of-speech tagging ( POS tagging or PoS tagging or POST), also called grammatical tagging is the process of marking up a word in a text (corpus) as corresponding to a particular part of speech, based on both its definition and its context.Ī simplified form of this is commonly taught to school-age children, in the identification of words as nouns, verbs, adjectives, adverbs, etc. JSTOR ( March 2021) ( Learn how and when to remove this template message).Unsourced material may be challenged and removed.įind sources: "Part-of-speech tagging" – news
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