Anna Feltracco


2018

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Enriching a Lexicon of Discourse Connectives with Corpus-based Data
Anna Feltracco | Elisabetta Jezek | Bernardo Magnini
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2016

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Acquiring Opposition Relations among Italian Verb Senses using Crowdsourcing
Anna Feltracco | Simone Magnolini | Elisabetta Jezek | Bernardo Magnini
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

We describe an experiment for the acquisition of opposition relations among Italian verb senses, based on a crowdsourcing methodology. The goal of the experiment is to discuss whether the types of opposition we distinguish (i.e. complementarity, antonymy, converseness and reversiveness) are actually perceived by the crowd. In particular, we collect data for Italian by using the crowdsourcing platform CrowdFlower. We ask annotators to judge the type of opposition existing among pairs of sentences -previously judged as opposite- that differ only for a verb: the verb in the first sentence is opposite of the verb in second sentence. Data corroborate the hypothesis that some opposition relations exclude each other, while others interact, being recognized as compatible by the contributors.

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FBK-HLT-NLP at SemEval-2016 Task 2: A Multitask, Deep Learning Approach for Interpretable Semantic Textual Similarity
Simone Magnolini | Anna Feltracco | Bernardo Magnini
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

2015

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Opposition Relations among Verb Frames
Anna Feltracco | Elisabetta Jezek | Bernardo Magnini
Proceedings of the The 3rd Workshop on EVENTS: Definition, Detection, Coreference, and Representation

2014

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T-PAS; A resource of Typed Predicate Argument Structures for linguistic analysis and semantic processing
Elisabetta Jezek | Bernardo Magnini | Anna Feltracco | Alessia Bianchini | Octavian Popescu
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

The goal of this paper is to introduce T-PAS, a resource of typed predicate argument structures for Italian, acquired from corpora by manual clustering of distributional information about Italian verbs, to be used for linguistic analysis and semantic processing tasks. T-PAS is the first resource for Italian in which semantic selection properties and sense-in-context distinctions of verbs are characterized fully on empirical ground. In the paper, we first describe the process of pattern acquisition and corpus annotation (section 2) and its ongoing evaluation (section 3). We then demonstrate the benefits of pattern tagging for NLP purposes (section 4), and discuss current effort to improve the annotation of the corpus (section 5). We conclude by reporting on ongoing experiments using semiautomatic techniques for extending coverage (section 6).