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Maria Antònia Martí

Maria Antònia Martí works on computational linguistics, with a focus on building and annotating language resources. Their papers here deal with coreference resolution and with semantic role labeling across languages. A recurring question is how annotation schemes should handle cases that do not fit clean categories. The work draws on corpora in English and Catalan, among other languages.

The most cited of these papers is The CoNLL-2009 Shared Task, an overview of a shared evaluation on joint dependency parsing and semantic role labelling. It carried an earlier English-only task over to Catalan, Chinese, Czech, German, Japanese and Spanish, using a common dependency format. It also offered closed and open challenges and added out-of-domain test sets for some languages. The next most cited, A Typology of Near-Identity Relations for Coreference, argues that coreference is better seen as a continuum than as a yes-or-no relation. It proposes near-identity as a middle category, for example a person versus a photograph of that person, and builds the NIDENT typology from examples found in real text.

The latest work, Annotating Near-Identity from Coreference Disagreements from 2012, tests that idea in practice. It adds near-identity labels to portions of the English NP4E corpus and the Catalan AnCora-CA corpus. Annotators rarely chose these labels when asked directly, so the paper also tries an indirect route that uses disagreement among annotators as the signal. Martí's papers are associated with Universitat de Barcelona. The coreference studies were written with Marta Recasens, and the CoNLL overview with a broad multilingual team including Jan Hajič and Lluís Màrquez.

Maria Antònia Martí has 3 papers in our library, in 2009–2012, most of them on Coreference resolution, Semantic role labeling, Multilingual & cross-lingual NLP; often with Marta Recasens, Adam Meyers, Constantin Orasan.

3 papers in our library · 2009–2012

OpenAlex · ORCID · Wikidata · h-index 21 · 168 works · 2,545 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 397 citations in our library · 6 more in our library without a page yet · ⭐ Paper Star rank #2403

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Topics

 Coreference resolution (2) Semantic role labeling (1) Multilingual & cross-lingual NLP (1)

 Works by year

2010s

2000s

 Papers

The most cited first (OpenAlex and our library).

  1. The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages (2009 · 631 citations)
    This is the overview of the 2009 CoNLL shared task on joint syntactic dependency parsing and semantic role labelling.
  2. A Typology of Near-Identity Relations for Coreference (NIDENT) (2010 · 67 citations)
    Coreference corpora such as ACE and OntoNotes sometimes annotate the same kind of example differently. The authors attribute this to a strict binary choice between identity and non-identity, which fails when two mentions denote almost the same discourse entity. Examples include a town before and after demographic…
  3. Annotating Near-Identity from Coreference Disagreements (2012 · 36 citations)
    Standard coreference corpora treat coreference as a yes/no relation. Borderline cases, where two mentions refer to "almost" the same entity, therefore cause annotator disagreement and add noise for resolution systems. The authors extend two existing coreference resources, the English NP4E and the Catalan AnCora-CA…

Also in our library

6 more works of theirs are in our library without a page here yet; they will appear as we publish them.

 Co-authors here

12 of 15 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 397 times (of the 140,884 papers whose bibliographies we read); 50 citing papers with a page here →.

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