Part-of-Speech Tagging › What Are Parts of Speech?
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Parts of speech, also called word classes or lexical categories, group words by their grammatical function and syntactic behavior. The classification dates to ancient Greek grammarians and was systematized by Pāṇini for Sanskrit around 400 BCE. Modern linguistics recognizes that word classes are defined by distributional properties: words that occupy the same syntactic positions and combine with the same kinds of modifiers belong to the same class.
A part of speech (POS) is a grammatical category assigned to a word based on its syntactic role and morphological properties. Major categories include nouns, verbs, adjectives, adverbs, determiners, prepositions, and conjunctions.
The traditional list of eight parts of speech taught in school (noun, verb, adjective, adverb, pronoun, preposition, conjunction, interjection) is a coarse-grained starting point. Computational linguistics requires finer distinctions. Instead of a single "verb" category, we need to distinguish base form verbs, past tense verbs, gerunds, past participles, and third-person singular present forms, because they behave differently in syntax and morphology.
The core intuition behind any POS system is that words group into categories based on:
- Distributional behavior: Nouns follow determiners ("the dog"), verbs follow noun phrases ("the dog barked")
- Morphological properties: Nouns form plurals (-s), verbs inflect for tense (-ed, -ing), adjectives form comparatives (-er)
- Semantic tendencies: Nouns typically name entities, verbs typically name events, adjectives name properties
These three criteria often agree but sometimes conflict, which is why POS classification requires careful linguistic thought.
It is worth pausing on why distributional behavior is the most reliable of these three criteria. Consider the word "table." Semantically it names a physical object, so you might guess it is always a noun. But "table the motion" is perfectly grammatical English where "table" functions as a verb. The semantic criterion would lead you astray. The distributional criterion works better: in "table the motion," "table" appears immediately after a subject noun phrase and before a direct object noun phrase, which is a verb position. The morphological criterion is also informative but incomplete: "table" has no distinctive verb morphology here, but English is a low-inflection language where verbs frequently appear in their bare stem form.
Computational systems that learn POS categories from annotated corpora are, implicitly, learning these distributional patterns. When a neural tagger encounters a word it has never seen before, its prediction is guided by the context words that surround it, not by any innate category knowledge. This distributional learning is one of the key mechanisms that allows modern taggers to handle out-of-vocabulary words gracefully.