Learning when to point : a data-driven approach

The relationship between how people describe objects and when they choose to point is complex and likely to be influenced by factors related to both perceptual and discourse context. In this paper, we explore these interactions using machine-learning on a dialogue corpus, to identify multimodal referential strategies that can be used in automatic multimodal generation. We show that the decision to use a pointing gesture depends on features of the accompanying description (especially whether it contains spatial information), and on visual properties, especially distance or separation of a referent from its previous referent.peer-reviewe

Inter-Coder Agreement for Computational Linguistics

This article is a survey of methods for measuring agreement among corpus annotators. It exposes the mathematics and underlying assumptions of agreement coefficients, covering Krippendorff's alpha as well as Scott's pi and Cohen's kappa; discusses the use of coefficients in several annotation tasks; and argues that weighted, alpha-like coefficients, traditionally less used than kappa-like measures in computational linguistics, may be more appropriate for many corpus annotation tasks—but that their use makes the interpretation of the value of the coefficient even harder. </jats:p

Editorial for the First Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics

The workshop "Mining Scientific Papers: Computational Linguistics and Bibliometrics" (CLBib 2015), co-located with the 15th International Society of Scientometrics and Informetrics Conference (ISSI 2015), brought together researchers in Bibliometrics and Computational Linguistics in order to study the ways Bibliometrics can benefit from large-scale text analytics and sense mining of scientific papers, thus exploring the interdisciplinarity of Bibliometrics and Natural Language Processing (NLP). The goals of the workshop were to answer questions like: How can we enhance author network analysis and Bibliometrics using data obtained by text analytics? What insights can NLP provide on the structure of scientific writing, on citation networks, and on in-text citation analysis? This workshop is the first step to foster the reflection on the interdisciplinarity and the benefits that the two disciplines Bibliometrics and Natural Language Processing can drive from it.Comment: 4 pages, Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics at ISSI 201

Computational coverage of type logical grammar: The Montague test

It is nearly half a century since Montague made his contributions to the field of logical semantics. In this time, computational linguistics has taken an almost entirely statistical turn and mainstream linguistics has adopted an almost entirely non-formal methodology. But in a minority approach reaching back before the linguistic revolution, and to the origins of computing, type logical grammar (TLG) has continued championing the flags of symbolic computation and logical rigor in discrete grammar. In this paper, we aim to concretise a measure of progress for computational grammar in the form of the Montague Test. This is the challenge of providing a computational cover grammar of the Montague fragment. We formulate this Montague Test and show how the challenge is met by the type logical parser/theorem-prover CatLog2.Peer ReviewedPostprint (published version