Towards Comprehensive Computational Representations of Arabic Multiword Expressions

A successful computational treatment of multiword expressions (MWEs) in natural languages leads to a robust NLP system which considers the long-standing problem of language ambiguity caused primarily by this complex linguistic phenomenon. The first step in addressing this challenge is building an extensive reliable MWEs language resource LR with comprehensive computational representations across all linguistic levels. This forms the cornerstone in understanding the heterogeneous linguistic behaviour of MWEs in their various manifestations. This paper presents a detailed framework for computational representations of Arabic MWEs (ArMWEs) across all linguistic levels based on the state-of-the-art lexical mark-up framework (LMF) with the necessary modifications to suit the distinctive properties of Modern Standard Arabic (MSA). This work forms part of a larger project that aims to develop a comprehensive computational lexicon of ArMWEs for NLP and language pedagogy LP (JOMAL project)

Data-based analysis of speech and gesture: the Bielefeld Speech and Gesture Alignment corpus (SaGA) and its applications

Lücking A, Bergmann K, Hahn F, Kopp S, Rieser H. Data-based analysis of speech and gesture: the Bielefeld Speech and Gesture Alignment corpus (SaGA) and its applications. Journal on Multimodal User Interfaces. 2013;7(1-2):5-18.Communicating face-to-face, interlocutors frequently produce multimodal meaning packages consisting of speech and accompanying gestures. We discuss a systematically annotated speech and gesture corpus consisting of 25 route-and-landmark-description dialogues, the Bielefeld Speech and Gesture Alignment corpus (SaGA), collected in experimental face-to-face settings. We first describe the primary and secondary data of the corpus and its reliability assessment. Then we go into some of the projects carried out using SaGA demonstrating the wide range of its usability: on the empirical side, there is work on gesture typology, individual and contextual parameters influencing gesture production and gestures’ functions for dialogue structure. Speech-gesture interfaces have been established extending unification-based grammars. In addition, the development of a computational model of speech-gesture alignment and its implementation constitutes a research line we focus on

Satisfying constraints on extraction and adjunction

In this paper, we present a unified feature-based theory of complement, adjunct, and subject extraction, in which there is no need either for valence reducing lexical rules or for phonologically null traces. Our analysis rests on the assumption that the mapping between argument structure and valence is defined by realization constraints which are satisfied by all lexical heads. Arguments can be realized as local dependents, in which case they are selected via the head's valence features. Alternatively, arguments may be realized in a long-distance dependency construction, in which case they are selected via the head's slash features. Furthermore, we argue that English post-verbal adjuncts, as well as complements, are syntactic dependents selected by the verb, thus providing a uniform analysis of complement and adjunct extraction. Finally, we show that our analysis provides an alternative treatment of subject extraction and we offer a new account of the that-trace effect

Learning designs as a stimulus and support for teachers\u27 design practices

This chapter builds on and brings up to date the work described in Chapter 6. The authors report on a decade of empirical work with teaching practitioners which has led them to conclude that learning designs (by which they mean a specific form of graphical representation and explanatory text) are usable by university teachers. Designs are referred to for guidance and inspiration, in what the authors see as an example of case-based professional learning. Having a classification system seems to support this, even though it is not directly related to subject area. An important finding is that learning designs from the AUTC project can support the integration of pedagogy, technology and content knowledge in practitioners\u27 design thinking

Putting the Horses before the Cart: Identifying Multiword Expressions before Translation

International audienceTranslating multiword expressions (MWEs) is notoriously difficult. Part of the challenge stems from the analysis of non-compositional expressions in source texts, preventing literal translation. Therefore, before translating them, it is crucial to locate MWEs in the source text. We would be putting the cart before the horses if we tried to translate MWEs before ensuring that they are correctly identified in the source text. This paper discusses the current state of affairs in automatic MWE identification, covering rule-based methods and sequence taggers. While MWE identification is not a solved problem, significant advances have been made in the recent years. Hence, we can hope that MWE identification can be integrated into MT in the near future, thus avoiding clumsy translations that have often been mocked and used to motivate the urgent need for better MWE processing

QuASIt: A cognitive inspired approach to question answering for the Italian language

In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt is both a rule-based and ontology-based question answering system. In the model, rules are aimed at understanding the query in terms of the linguistic typology of the question, and enabling its semantic processing as regards the search for the answer in the structured knowledge from DBPedia Italian project. Also the free explicative text in support of the query is analyzed if available. QuASIt attempts to answer for both multiple choice and essay questions. The model is presented, the implementation of the system is detailed, and some experiments are discussed