Patricia Gonçalves

Also published as: Patrícia Gonçalves, Patricia Nunes Gonçalves


Fixing paper assignments

  1. Please select all papers that do not belong to this person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here


2014

pdf bib
Answering List Questions using Web as a corpus
Patrícia Gonçalves | António Branco
Proceedings of the Demonstrations at the 14th Conference of the European Chapter of the Association for Computational Linguistics

2012

pdf bib
Treebanking by Sentence and Tree Transformation: Building a Treebank to support Question Answering in Portuguese
Patrícia Gonçalves | Rita Santos | António Branco
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper presents CINTIL-QATreebank, a treebank composed of Portuguese sentences that can be used to support the development of Question Answering systems. To create this treebank, we use declarative sentences from the pre-existing CINTIL-Treebank and manually transform their syntactic structure into a non-declarative sentence. Our corpus includes two clause types: interrogative and imperative clauses. CINTIL-QATreebank can be used in language science and techology general research, but it was developed particularly for the development of automatic Question Answering systems. The non-declarative entences are annotated with several layers of linguistic information, namely (i) trees with information on constituency and grammatical function; (ii) sentence type; (iii) interrogative pronoun; (iv) question type; and (v) semantic type of expected answer. Moreover, these non-declarative sentences are paired with their declarative counterparts and associated with the expected answer snippets.

2011

pdf bib
Uma abordagem de classificação automática para Tipo de Pergunta e Tipo de Resposta (An Automatic Approach for Classification of Question Type and Answer Type) [in Portuguese]
Patricia Nunes Gonçalves | António Horta Branco
Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology

2010

pdf bib
Top-Performing Robust Constituency Parsing of Portuguese: Freely Available in as Many Ways as you Can Get it
João Silva | António Branco | Patricia Gonçalves
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

In this paper we present LX-Parser, a probabilistic, robust constituency parser for Portuguese. This parser achieves ca. 88% f-score in the labeled bracketing task, thus reaching a state-of-the-art performance score that is in line with those that are currently obtained by top-ranking parsers for English, the most studied natural language. To the best of our knowledge, LX-Parser is the first state-of-the-art, robust constituency parser for Portuguese that is made freely available. This parser is being distributed in a variety of ways, each suited for a different type of usage. More specifically, LX-Parser is being made available (i) as a downloadable, stand-alone parsing tool that can be run locally by its users; (ii) as a Web service that exposes an interface that can be invoked remotely and transparently by client applications; and finally (iii) as an on-line parsing service, aimed at human users, that can be accessed through any common Web browser.