Objective
The exponential growth of the Web is resulting in vast amounts of online content. However, the
information expressed therein is not at easy reach: what we typically browse is only an infinitesimal part
of the Web. And even if we had time to read all the Web we could not understand it, as most of it is
written in languages we do not speak. Computers, instead, have the power to process the entire Web.
But, in order to ”read” it, that is perform machine reading, they still have to face the hard problem of
Natural Language Understanding, i.e. automatically making sense of human language. To tackle this
long-lasting challenge in Natural Language Processing (NLP), the task of semantic parsing has recently
gained popularity. This aims at creating structured representations of meaning for an input text. However,
current semantic parsers require supervision, binding them to the language of interest and hindering their
extension to multiple languages.
Here we propose a research program to investigate radically new directions for enabling multilingual
semantic parsing, without the heavy requirement of annotating training data for each new language.
The key intuitions of our proposal are treating multilinguality as a resource rather than an obstacle and
embracing the knowledge-based paradigm which allows supervision in the machine learning sense to be
replaced with efficacious use of lexical knowledge resources. In stage 1 of the project we will acquire
a huge network of language-independent, structured semantic representations of sentences. In stage 2,
we will leverage this resource to develop innovative algorithms that perform semantic parsing in any
language. These two stages are mutually beneficial, progressively enriching less-resourced languages and
contributing towards leveling the playing field for all languages. Enabling Natural Language Understanding
across languages should have an impact on NLP and other areas of AI, plus a societal impact on language
learners.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- humanities languages and literature general language studies
- natural sciences computer and information sciences data science natural language processing
- natural sciences computer and information sciences artificial intelligence machine learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-COG - Consolidator Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2016-COG
See all projects funded under this callHost institution
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
00185 Roma
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.