Formal Distributional Semantics: Introduction to the Special Issue

Author:

Boleda Gemma1,Herbelot Aurélie1

Affiliation:

1. University of Trento

Abstract

Formal Semantics and Distributional Semantics are two very influential semantic frameworks in Computational Linguistics. Formal Semantics is based on a symbolic tradition and centered around the inferential properties of language. Distributional Semantics is statistical and data-driven, and focuses on aspects of meaning related to descriptive content. The two frameworks are complementary in their strengths, and this has motivated interest in combining them into an overarching semantic framework: a “Formal Distributional Semantics.” Given the fundamentally different natures of the two paradigms, however, building an integrative framework poses significant theoretical and engineering challenges. The present issue of Computational Linguistics advances the state of the art in Formal Distributional Semantics; this introductory article explains the motivation behind it and summarizes the contributions of previous work on the topic, providing the necessary background for the articles that follow.

Publisher

MIT Press - Journals

Subject

Artificial Intelligence,Computer Science Applications,Linguistics and Language,Language and Linguistics

Reference64 articles.

1. Baroni, Marco, Raffaella Bernardi, Ngoc-Quynh Do, and Chung-chieh Shan. 2012. Entailment above the word level in distributional semantics. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics, pages 23–32, Avignon.

2. Baroni, Marco, Raffaella Bernardi, and Roberto Zamparelli. 2015. Frege in space: A program for compositional distributional semantics. Linguistic Issues in Language Technology, 9:5–110.

3. Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors

4. Distributional Memory: A General Framework for Corpus-Based Semantics

5. Baroni, Marco and Roberto Zamparelli. 2010. Nouns are vectors, adjectives are matrices: Representing adjective-noun constructions in semantic space. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP2010), pages 1183–1193, MIT, MA.

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