University of Oxford Logo University of OxfordDepartment of Computer Science - Home

Compositional Distributional Models of Meaning

Where natural language semantics meets quantum information flow...

Computing Compositionality with Diagrams

The problem of representing natural language meaning in a computationally tractable way has been approached in various and often mutually incompatible ways. Two such orthogonal classes of semantic representation are distributional and symbolic models of meaning. Distributional models of meaning exploit the co-occurrence of other terms with the term being modelled to determine its semantic content, applying Firth's well-known dictum that "You shall know a word by the company it keeps"; while the symbolic approach usually exploits grammatical features of sentences to model relations between entities in the world, thereby expressing the truth conditions of sentences.

These approaches seem theoretically orthogonal, and hence incompatible in implementation. Distributional models of meaning are quantitative and express the semantic relation between terms but offering no immediately obvious way of modelling the contribution of sentence structure to meaning; while typically the semantics of individual words in qualitative symbolic approaches is left "mysterious" and ill-defined.

This project seeks to reconcile these apparently orthogonal representations, guided by the intuition that lexical co-relation and grammatical roles both correspond to different ways of "knowing how to use" language, thus both aspects provide relevant information when we understand the meaning of an expression, and hence they are viable components for a new representation modelling natural language semantics. Category theoretic methods from quantum information theory provide the building blocks for a general framework in which to combine symbolic and distributional approaches to expressing and comparing the meaning of sentences.

In bringing together expertise from the fields of formal logic, philosophy of language, computational linguistics, pure mathematics and theoretical physics, this project aims to produce a new model of natural language semantics for use in the development of more sophisticated text processing applications, document retrieval systems, intelligent agents, etc.

Project Link

EPSRC LogoThis research is currently supported by the EPSRC (grant EP/I03808X/1) as part of a multi-site grant (Cambridge, Edinburgh, Oxford, Sussex, York) for the project A Unified Model of Compositional and Distributional Semantics: Theory and Applications.

A public mailing list, disco-news@maillist.ox.ac.uk, has been created for interested parties wanting to receive updates about the project regarding publications, workshops, conference talks and other matters. This mailing list can be joined by emailing disco-news-subscribe@maillist.ox.ac.uk.

An internal mailing list exists for local activity participants. To be added please contact Ed Grefenstette.

External Collaborators

Past Events

Upcoming Events

Datasets

People

Faculty

Research

Students

Selected Publications

View all

Experimental Support for a Categorical Compositional Distributional Model of Meaning

Edward Grefenstette and Mehrnoosh Sadrzadeh

In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing. 2011.

Experimenting with Transitive Verbs in a DisCoCat

Edward Grefenstette and Mehrnoosh Sadrzadeh

In Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics. 2011.

A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations

Mehrnoosh Sadrzadeh and Edward Grefenstette

In Lecture Notes in Computer Science. Vol. 7052. Pages 35–47. 2011.

Info

Themes