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Jost Gippert: Our Featured Linguist!

"Buenos dias", "buenas noches" -- this was the first words in a foreign language I heard in my life, as a three-year old boy growing up in developing post-war Western Germany, where the first gastarbeiters had arrived from Spain. Fascinated by the strange sounds, I tried to get to know some more languages, the only opportunity being TV courses of English and French -- there was no foreign language education for pre-teen school children in Germany yet in those days. Read more



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What is English? And Why Should We Care?

By: Tim William Machan

To find some answers Tim Machan explores the language's present and past, and looks ahead to its futures among the one and a half billion people who speak it. His search is fascinating and important, for definitions of English have influenced education and law in many countries and helped shape the identities of those who live in them.


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Medical Writing in Early Modern English

Edited by Irma Taavitsainen and Paivi Pahta

This volume provides a new perspective on the evolution of the special language of medicine, based on the electronic corpus of Early Modern English Medical Texts, containing over two million words of medical writing from 1500 to 1700.


Academic Paper


Title: A comparison of parsing technologies for the biomedical domain
Author: Claire Grover
Institution: University of Edinburgh
Author: Alex Lascarides
Homepage: http://www.cogsci.ed.ac.uk/~alex/
Institution: University of Edinburgh
Author: Mirella Lapata
Institution: University of Sheffield
Linguistic Field: Computational Linguistics
Abstract: This paper reports on a number of experiments which are designed to investigate the extent to which current NLP resources are able to syntactically and semantically analyse biomedical text. We address two tasks: (a) parsing a real corpus with a hand-built wide-coverage grammar, producing both syntactic analyses and logical forms and (b) automatically computing the interpretation of compound nouns where the head is a nominalisation (e.g. hospital arrival means an arrival at hospital, while patient arrival means an arrival of a patient). For the former task we demonstrate that flexible and yet constrained pre-processing techniques are crucial to success: these enable us to use part-of-speech tags to overcome inadequate lexical coverage, and to package up complex technical expressions prior to parsing so that they are blocked from creating misleading amounts of syntactic complexity. We argue that the XML-processing paradigm is ideally suited for automatically preparing the corpus for parsing. For the latter task, we compute interpretations of the compounds by exploiting surface cues and meaning paraphrases, which in turn are extracted from the parsed corpus. This provides an empirical setting in which we can compare the utility of a comparatively deep parser vs. a shallow one, exploring the trade-off between resolving attachment ambiguities on the one hand and generating errors in the parses on the other. We demonstrate that a model of the meaning of compound nominalisations is achievable with the aid of current broad-coverage parsers.

CUP at LINGUIST

This article appears in Natural Language Engineering Vol. 11, Issue 1, which you can read on Cambridge's site or on LINGUIST .



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