Semantically Related Words Extraction Task

A Semantically Related Words Extraction Task is an information extraction task that is required to create clusters of semantically related words.

• Context:
  • Input: A Linguistic Dataset (e.g. a corpus or a word set).
    • optional: A Lexicon.
• Example(s):
  • a Synonym Extraction Task.
  • an Antonym Extraction Task.
  • …
• Counter-Example(s):
  • a Syntactically Related Words Extraction Task.
  • a Noun-Phrase Coreference Resolution Task.
  • a Terminology Extraction Task.
  • a Weakly-Supervised Class Population Task (see more-like-this task).
  • a Hypernym Extraction Task.
• See: Lexical Semantic Relationship Measure.

---

---

References

2012

• (Wang & Hirst, 2012) ⇒ Tong Wang, and Graeme Hirst. (2012). “Exploring Patterns in Dictionary Definitions for Synonym Extraction.” In: Natural Language Engineering, 18(03).
  • ABSTRACT: Automatic determination of synonyms and/or semantically related words has various applications in Natural Language Processing. Two mainstream paradigms to date, lexicon-based and distributional approaches, both exhibit pros and cons with regard to coverage, complexity, and quality. In this paper, we propose three novel methods — two rule-based methods and one machine learning approach — to identify synonyms from definition texts in a machine-readable dictionary. Extracted synonyms are evaluated in two extrinsic experiments and one intrinsic experiment. Evaluation results show that our pattern-based approach achieves best performance in one of the experiments and satisfactory results in the other, comparable to corpus-based state-of-the-art results.

---