Opendata, web and dolomites


A Theory of Reference for Distributional Semantics

Total Cost €


EC-Contrib. €






Project "ThReDS" data sheet

The following table provides information about the project.


Organization address
address: PLACA DE LA MERCE, 10-12
postcode: 8002

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website
 Total cost 158˙121 €
 EC max contribution 158˙121 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2017
 Duration (year-month-day) from 2017-07-01   to  2019-06-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSIDAD POMPEU FABRA ES (BARCELONA) coordinator 158˙121.00


 Project objective

One of the most fundamental human faculties is 'reference': the capacity to 'talk about things'. This extraordinary ability is at the core of many forms of human exchange, from asking for the salt at the dinner table to collaboratively building a solar probe. It involves using linguistic signs to identify things in the world and bring them to the mind of another. Reference is poorly understood: in particular, we do not know how humans build a shared linguistic representation of their environment, which they use to link words and world. My goal is to build a computational model of the way people acquire world knowledge from language and translate knowledge back into language. My overall framework includes three steps: 1) creating a representation of the way people 'talk about things', using distributional semantics (DS: a computational approach to modelling word usage); 2) automatically mapping the distributional model onto a partial set-theoretic model (a formal knowledge representation expressing shared beliefs about the world); 3) using the set-theoretic model to generate unobserved linguistic expressions which refer. The pipeline will be evaluated via an online game where a computer has to produce references to well-known concepts and individuals for a human tester. This work will significantly advance the state-of-the-art in linguistics: while DS has enjoyed considerable success in modelling lexical phenomena, it is currently showing its limits in explaining referential aspects of meaning. Conversely, referential semantics is still far from fully explaining the cognitive aspects of concept acquisition and reuse. The proposed investigation requires a very novel integration of computational semantics (my area of expertise) and formal linguistics (in which my host is an internationally recognised expert). The collaboration will give us the chance to lead a burgeoning area of research aiming at integrating reference into DS.


year authors and title journal last update
List of publications.
2017 Aurelie Herbelot and Marco Baroni
High-risk learning: acquiring new word vectors from tiny data
published pages: , ISSN: , DOI:
Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP2017) 2019-06-11

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The information about "THREDS" are provided by the European Opendata Portal: CORDIS opendata.

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