Rule-based Part-of-Speech Tagging System

A Rule-based Part-of-Speech Tagging System is a Part-of-Speech Tagging System that uses a predefined set of contextual and lexical rules.

• AKA: Rule-based POS Tagging System, Ruler-based Tagger.
• Example(s):
  • …
• Counter-Example(s):
  • a Stochastic Part-of-Speech Tagging System,
  • a Phrasal Chunking System,
  • a Word Mention Tagging System,
  • a Co-Reference Resolution System,
  • a Chunking System.
• See: Natural Language Processing System, Word Sense Disambiguation System, Noun, Verb, Pronoun, Adjective, Morphology, Syntax, Lexicon.

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References

1992

• (Brill, 1992) ⇒ Eric D. Brill. (1992). “A Simple Rule-based Part of Speech Tagger.” In: Proceedings of the Conference on Applied Natural Language Processing (ANLP 1992).
  • QUOTE: A number of rule-based taggers have been built [Klein and Simmons 63, Green and Rubin 71, Hindle 89]. [Klein and Simmons 63] and [Green and Rubin 71] both have error rates substantially higher than state of the art stochastic taggers. [Hindle 89] disambiguates words within a deterministic parser. We wanted to determine whether a simple rule-based tagger without any knowledge of syntax can perform as well as a stochastic tagger, or if part of speech tagging really is a domain to which stochastic techniques are better suited.

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