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Linguistic Diversity and Social Justice

By Ingrid Piller

Linguistic Diversity and Social Justice "prompts thinking about linguistic disadvantage as a form of structural disadvantage that needs to be recognized and taken seriously."


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Language Evolution: The Windows Approach

By Rudolf Botha

Language Evolution: The Windows Approach addresses the question: "How can we unravel the evolution of language, given that there is no direct evidence about it?"


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Academic Paper


Title: A machine learning approach to textual entailment recognition
Author: Fabio Massimo Zanzotto
Institution: Università degli Studi di Roma - La Sapienza
Author: Marco Pennacchiotti
Institution: Yahoo! Research
Author: Alessandro Moschitti
Institution: Università degli Studi di Trento
Linguistic Field: Computational Linguistics; Pragmatics; Semantics; Syntax
Abstract: Designing models for learning textual entailment recognizers from annotated examples is not an easy task, as it requires modeling the semantic relations and interactions involved between two pairs of text fragments. In this paper, we approach the problem by first introducing the class of pair feature spaces, which allow supervised machine learning algorithms to derive first-order rewrite rules from annotated examples. In particular, we propose syntactic and shallow semantic feature spaces, and compare them to standard ones. Extensive experiments demonstrate that our proposed spaces learn first-order derivations, while standard ones are not expressive enough to do so.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 15, Issue 4, which you can READ on Cambridge's site or on LINGUIST .



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