LINGUIST List 20.1609
|
Mon Apr 27 2009
Calls: Semantics,Computational Ling,Text/Corpus Ling/Singapore
Editor for this issue: Elyssa Winzeler
<elyssa linguistlist.org>
|
LINGUIST is pleased to announce the launch of an exciting new feature: Easy Abstracts! Easy Abs is a free abstract submission and review facility designed to help conference organizers and reviewers accept and process abstracts online. Just go to: http://www.linguistlist.org/confcustom, and begin your conference customization process today! With Easy Abstracts, submission and review will be as easy as 1-2-3!
|
Directory
1. Elyssa
Winzeler,
Multiword Expressions
Message 1: Multiword Expressions
|
Date: 26-Apr-2009
From: Elyssa Winzeler <elyssa linguistlist.org>
Subject: Multiword Expressions
E-mail this message to a friend
Full Title: Multiword Expressions Short Title: MWE 09 Date: 06-Aug-2009 - 06-Aug-2009 Location: Singapore, Singapore Contact Person: Dimitra Anastasiou Meeting Email: dimitra d-anastasiou.com Web Site: http://multiword.sourceforge.net/PHITE.php?sitesig=CONF&page=CONF_40_MWE_2009___lb__ACL__rb__ Linguistic Field(s): Applied Linguistics; Computational Linguistics; Discourse Analysis; General Linguistics; Morphology; Semantics; Syntax; Text/Corpus Linguistics; Translation Call Deadline: 04-May-2009 Meeting Description: Multi-Word Expressions (MWEs) are an indispensable part of natural languages and appear steadily on a daily basis, both new and already existing but paraphrased. Thus, the automated processing of MWEs is important for many natural language applications. The meaning of MWEs can be either motivated or arbitrary. Native speakers master most MWEs, while learners of a foreign language have to learn MWEs by heart. The interpretation of MWEs poses a major challenge for automated analysis helping both groups easily master MWEs. The growing interest in MWEs in the NLP community has led to many specialized workshops held every year since 2001 in conjunction with ACL, EACL and LREC; there have been also two recent special issues on MWEs published by leading journals: the International Journal of Language Resources and Evaluation, and the Journal of Computer Speech and Language. As a result of the overall progress in the field, the time has come to move from basic preliminary research to actual applications in real-world NLP tasks. Following this trend, the LREC-MWE'08 focused on gathering resources and creating a common repository in order to rank MWE candidates and facilitate further research. Call for Papers Deadline Extended to May 4, 2009 In MWE'09 we are interested in the overall process of dealing with MWEs, asking for original research related (but not limited) to the following four fundamental topics. (1) Identification. Identification is a major problem for MWEs. The MWE identification task is to determine whether a MWE is used non-compositionally (figuratively) or compositionally (literally) in a particular context. The identification of MWEs by automated means is a difficult task, as it does not suffice to store the MWE into a dictionary database. Rule-based (morphosyntactic rules) and/or statistical approaches may be needed to identify MWEs in context. (2) Interpretation. Semantic interpretation of MWEs, particularly noun compounds and determinerless prepositional phrases, is the task of determining the implicit semantic relation holding between the MWE's sub-components. This specific area is inviting research on (linguistically) identifying the semantic relations (SRs) and automatic SR interpretation in MWEs. The relation inventories used can be of different granularity and dependent on the particular type of MWE construction. In some cases, MWE's semantics can be also specified in terms of a suitable paraphrase. (3) Disambiguation. Disambiguation (Semantic classification) is the task of specifying the semantics of MWEs based on an inventory of semantic relations. It tends to presuppose the ability to classify the (degree of) compositionality of MWEs and applies only to compositional MWEs. The aim is to specify the semantics of MWEs in terms of predefined semantic categories, e.g., in WordNet. (4) Applications. Identifying MWEs in context and understanding their syntax and semantics is important for many natural language applications, including but not limited to question answering, machine translation, information retrieval, information extraction, and textual entailment. Still, despite the growing research interest, there are not enough successful applications in real NLP problems, which we believe is the key for the advancement of the field.
Read more issues|LINGUIST home page|Top of issue
|
|

Please report any bad links or misclassified data
LINGUIST Homepage | Read
LINGUIST | Contact us

While the LINGUIST List makes every effort to ensure the linguistic relevance of sites listed on its pages, it cannot vouch for their contents.
|
|