Explore the words cloud of the DALI project. It provides you a very rough idea of what is the project "DALI" about.
The following table provides information about the project.
Coordinator |
QUEEN MARY UNIVERSITY OF LONDON
Organization address contact info |
Coordinator Country | United Kingdom [UK] |
Total cost | 2˙499˙471 € |
EC max contribution | 2˙499˙471 € (100%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2015-AdG |
Funding Scheme | ERC-ADG |
Starting year | 2016 |
Duration (year-month-day) | from 2016-09-01 to 2021-08-31 |
Take a look of project's partnership.
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1 | QUEEN MARY UNIVERSITY OF LONDON | UK (LONDON) | coordinator | 2˙197˙167.00 |
2 | UNIVERSITY OF ESSEX | UK (COLCHESTER) | participant | 302˙303.00 |
Natural language expressions are supposed to be unambiguous in context. Yet more and more examples of use of expressions that are ambiguous in context, yet felicitous and rhetorically unmarked, are emerging. In my own work, I demonstrated that ambiguity in anaphoric reference is ubiquitous, through the study of disagreements in annotation, that I pioneered in CL. Since then, additional cases of ambiguous anaphoric reference have been found; and similar findings have been made for other aspects of language interpretation, including wordsense disambiguation, and even part-of-speech tagging. Using the Phrase Detectives Game-With-A-Purpose to collect massive amounts of judgments online, we found that up to 30% of anaphoric expressions in our data are ambiguous. These findings raise a serious challenge for computational linguistics (CL), as assumptions about the existence of a single interpretation in context are built in the dominant methodology, that depends on a reliably annotated gold standard. The goal of the proposed project is to tackle this fundamental issue of disagreements in interpretation by using computational methods for collecting and analysing such disagreements, some of which already exist but have never before been applied in linguistics on a large scale, some we will develop from scratch. Specifically, I propose to develop more advanced games-with-a-purpose to collect massive amounts of data about anaphora from people playing a game. I propose to use Bayesian models of annotation, widely used in epidemiology but not in linguistics, to analyse such data and identify genuine ambiguities; doing this for anaphora will require novel methods. Third, I propose to use these data to revisit current theories about anaphoric expressions that do not seem to cause infelicitousness when ambiguous. Finally, I propose to develop the first supervised approach to anaphora resolution that does not require a gold standard as a blueprint for other areas.
year | authors and title | journal | last update |
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2018 |
Massimo Poesio, Yulia Grishina, Varada Kolhatkar,Nafise Sadat Moosavi, Ina Roesiger, Adam Roussel, Fabian Simonjetz, Alexandra Uma,Olga Uryupina, Juntao Yu, Heike Zinsmeister Anaphora Resolution with the ARRAU corpus published pages: , ISSN: , DOI: |
Proceedings of the NAACL Workshop on Computational Models of Reference, Anaphora and Coreference | 2019-10-09 |
2018 |
Silviu Paun, Jon Chamberlain, Udo Kruschwitz, Juntao Yu, Massimo Poesio A probabilistic annotation model for crowdsourcing coreference published pages: 1926-1937, ISSN: , DOI: |
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing | 2019-10-09 |
2018 |
Jon Chamberlain, Udo Kruschwitz, Massimo Poesio Optimising crowdsourcing efficiency: Amplifying human computation with validation published pages: 41-49, ISSN: 2196-7032, DOI: 10.1515/itit-2017-0020 |
it - Information Technology 60/1 | 2019-10-09 |
2019 |
Olga Uryupina, Ron Artstein, Antonella Bristot, Federica Cavicchio, Francesca Delogu, Kepa Rodriguez, and Massimo Poesio Annotating a broad range of anaphoric phenomena, in a variety of genres: the ARRAU corpus published pages: , ISSN: 1351-3249, DOI: |
Natural Language Engineering | 2019-10-09 |
2018 |
Silviu Paun, Bob Carpenter, Jon Chamberlain, Dirk Hovy, Udo Kruschwitz, Massimo Poesio Comparing Bayesian Models of Annotation published pages: 571-585, ISSN: 2307-387X, DOI: |
Transactions of the Association for Computational Linguistics | 2019-10-09 |
2017 |
Chris Madge, Jon Chamberlain, Udo Kruschwitz, Massimo Poesio Experiment-Driven Development of a GWAP for Marking Segments in Text published pages: , ISSN: , DOI: |
Proceedings of the CHIPLAY Conference | 2019-06-13 |
2017 |
Chris Madge, Richard Bartle, Jon Chamberlain, Udo Kruschwitz, Massimo Poesio Testing game mechanics in games with a purpose for NLP applications published pages: , ISSN: , DOI: |
Proceedings of the GAMES4NLP Symposium | 2019-06-13 |
2017 |
Jon Chamberlain, Richard Bartle, Udo Kruschwitz, Chris Madge, Massimo Poesio Metrics of games-with-a-purpose for NLP applications published pages: , ISSN: , DOI: |
Proceedings of GAMES4NLP 2017 | 2019-06-13 |
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The information about "DALI" are provided by the European Opendata Portal: CORDIS opendata.