Abstract:

The goal is to advance on computational models of meaning and their evaluation. We [...]]]>

This is the first Lexical Knowledge Base [...]]]> Machines need computing tools that are more powerful than conventional dictionaries for tasks like information extraction, disambiguation of word meanings, etc. This is in fact the function of the Euskal WordNet application —developed by the IXA Group (UPV/EHU)— which can already be consulted and downloaded free of charge.

This is the first Lexical Knowledge Base (LKB) developed for the Basque language: a “semantic dictionary” or “store” that compiles and organises lexical and semantic information. “It’s like a database, but the difference is that it not only gathers the usual information of a dictionary —the meanings of words and their corresponding definitions and examples—, it also links the concepts with each other,” pointed out Eneko Agirre, an IXA Group computer programmer.

If we look up the entry hatz (“finger”, “digit” or “toe” in Basque), the result is as follows: “Each of the five appendages at the end of human hands and feet.” That is what the term means. But apart from this information, we can get much more: the finger/toe is an appendage of the body; the thumb is a finger; fingers are part of the hand; hands, in turn, are part of the arm and fingers are used to touch objects, etc. In short: all the concepts are interrelated hierarchically. Every concept is also related to its equivalents in other languages: digit, hatz, dedo, dixito and dit.

Consulting the word hatz in Basque WordNet.

This database is tremendously useful in various fields, like machine translation, information extraction, disambiguation of word meanings and for question-answer systems. In machine translation, for example, the system has to understand which word it is translating, a task for which it needs a “semantic dictionary” of this type. “For a quality translation, it is necessary to be able to distinguish the most appropriate meaning from among the various ones,” stressed Agirre.

“Our aim (within the framework of QTLeap European project) is to improve the quality of machine translations by using WordNet,” he pointed out.

Over the 2014-2015 academic year, the university Master’s degree in Language Analysis and Processing (LAP) that the IXA Group will be running at the UPV/EHU will be studying the Basque WordNet and other language technologies used to develop similar applications.

Master’s in Language Analysis and Processing (LAP)

The aim of the University Master’s in Language Analysis and Processing is to analyse language and to learn about the techniques and applications available for processing it with the help of the computer.

This Master’s has been organised by the UPV/EHU’s IXA Group and is geared towards anybody who combines linguistics and computing: philologists and linguistics experts, computing and telecommunications engineers, mathematicians, translators, etc. To apply for it, it is enough to be in possession of a University degree, have some experience and display some interest in the subject.

The Master’s will take one year and a half and the classes will be held at the Computing Faculty of the UPV/EHU-University of the Basque Country. It will be possible to spread it over two or three academic years (to cater for professionals who are working).

The pre-registration period is already open, and applications will be accepted until June 30. For further information on the Master’s, please check out http://ixa.si.ehu.es/master/.

Our colleague Arantxa Otegi won last Janaury the III. Koldo MItxelena Award for PhD Theses organized by Euskaltzaindia (the Academy of Basque Language) and the University of the Basque Country.

CONGRATULATIONS Arantxa!

Congratulations to her supervisors (Xabier Arregi and Eneko Agirre).

The title of this thesis is ‘Expansion for information retrieval: contribution of word [...]]]>

Our colleague Arantxa Otegi won last Janaury the III. Koldo MItxelena Award for PhD Theses organized by Euskaltzaindia (the Academy of Basque Language) and the University of the Basque Country.

CONGRATULATIONS Arantxa!

Congratulations to her supervisors (Xabier Arregi and Eneko Agirre).

The title of this thesis is ‘Expansion for information retrieval: contribution of word sense disambiguation and semantic relatedness’.

The whole text is available here. This is the abstract:

Information retrieval (IR) aims at searching documents which satisfy the information need of an user. In that way, an IR system informs the user about relevant documents, that is those documents that contain the information they need as formulated in the query. Well-known search engines like Google and Yahoo are prime examples of IR systems.
A perfect IR system should retrieve only, and all, the relevant documents, rejecting the non-relevant ones. However, perfect retrieval systems do not exist. One of the main problems is the so-called vocabulary mismatch problem between query and documents: some documents might be relevant to the query even if the specific terms used differ substantially, or some documents might not be relevant to the query even they have some terms in common. The former is because several words or phrases can be used to express the same idea or item (synonymy). The latter is caused by ambiguity, where one word can have more than one interpretation depending on the context. Owing to these facts, if an IR system relies only on terms occurring in both the query and the document when it comes to deciding whether a document is relevant, it might be diffcult to fnd some of the interesting documents, and also to reject non-relevant documents. It seems fair to think that there will be more chances of successful retrieval if the meaning of the text is also taken into account.
Even though the vocabulary mismatch problem has been widely discussed in the literature from the early days of IR it remains unsolved, and most search engines just ignore it. This PhD dissertation explores whether natural language processing (NLP) can be used to alleviate this problem.
In a nutshell, we expand queries and documents making use of two NLP techniques, word sense disambiguation and semantic relatedness. For each of the mentioned techniques we propose an expansion strategy, in which we obtain synonyms and other related words for the words in the query and documents. We also present, for each case, a method to combine the expansions and original words effectively in an IR system. Furthermore, as the expansion technique we propose is useful for translating queries and documents, we show how a cross lingual information retrieval system could be improved using such an expansion technique.

Our extensive experiments on three datasets show that the expansion methods explored in this dissertation help overcome the mismatch problem, consequently improving the effectiveness of an IR system.

Title: Beyond Shallow Semantics. Date: October 8, 2012 Time: 16:00-19:00 Where: Computer Science Faculty, Room 3.2

Abstract

Shallow semantic analyzers, such as semantic role labelers and sense taggers, are increasing in accuracy and becoming commonplace. However, they only provide limited and local representations of [...]]]> Speaker:  Martha Palmer.  Department of Linguistics, University of Colorado (AEB)

Title: Beyond Shallow Semantics.
Date: October 8, 2012
Time: 16:00-19:00
Where: Computer Science Faculty, Room 3.2

Abstract

Shallow semantic analyzers, such as semantic role labelers and sense taggers, are increasing in accuracy and becoming commonplace. However, they only provide limited and local representations of words and individual predicate-argument structures. This talk will address some of the current opportunities and challenges in producing deeper, richer representations of coherent eventualities. Available resources, such as VerbNet, that can assist in this process will also be discussed, as well as some of their limitations.

Speaker’s bio

She is a Full Professor at the University of Colorado with joint appointments in Linguistics and Computer Science and is an Institute of Cognitive Science Faculty Fellow. She recently won a Boulder Faculty Assembly 2010 Research Award. Her research has been focused on trying to capture elements of the meanings of words that can comprise automatic representations of complex sentences and documents. Supervised machine learning techniques rely on vast amounts of annotated training data so she and her students are engaged in providing data with word sense tags and semantic role labels for English, Chinese, Arabic, Hindi, and Urdu, funded by DARPA and NSF. They also train automatic sense taggers and semantic role labelers, and extract bilingual lexicons from parallel corpora.

A more recent focus is the application of these methods to biomedical journal articles and clinical notes, funded by NIH. She is a co-editor for the Journal of Natural Language Engineering and for LiLT, Linguistic Issues in Language Technology, and on the CLJ Editorial Board. She is a past President of the Association for Computational Linguistics, past Chair of SIGLEX and SIGHAN, and was the Director of the 2011 Linguistics Institute held in Boulder, Colorado.

ACL special interest groups SIGLEX and SIGSEM are organising a joint conference on Lexical and computational semantics: *SEM

Eneko Agirre from the Ixa Group is the general chair in this conference.

The main goal of *SEM is to provide a stable fo of rum for the growing number of NLP researchers working on different [...]]]>

ACL special interest groups SIGLEX and SIGSEM are organising a joint conference on Lexical and computational semantics: *SEM

Eneko Agirre from the Ixa Group is the general chair in this conference.

The main goal of *SEM is to provide a stable fo of rum for the growing number of NLP researchers working on different aspects of semantic processing, which has been scattered over a large array of small workshops and conferences.

The first edition of *SEM will be a two-day conference collocated with the North American Chapter of the Association for Computational Linguistics and Human Language Technologies 2012 conference (NAACL HLT), which will take place in Montreal, Canada.

Important dates:
 30 March 2012, Paper due date
 23 April 2012, Notification of acceptance
  4 May 2012, Camera-ready deadline
7-8 June 2012, Conference

For further information see *SEM