[Corpora-List] Call for paper, TAL Journal, special issue on 'Named Entity and relations'

Sophie Rosset sophie.rosset
Mon Jan 28 22:29:25 CET 2013


[apologies for cross posting]

FIRST CALL FOR PAPERS

NAMED ENTITY, NAMED ENTITY RECOGNITION, NAMED ENTITY RELATION

A SPECIAL SPECIAL ISSUE OF THE < TRAITEMENT AUTOMATIQUE DES LANGUES > (TAL) JOURNAL http://www.atala.org/-Revue-TAL

Guest editors:

Sophia Ananiadou (Sophia.ananiadou at manchester.ac.uk) Nathalie Friburger (nathalie.friburger at univ-tours.fr) Sophie Rosset (sophie.rosset at limsi.fr)

We wish to invite papers on new research relating to Named Entities (NEs), their recognition (NER) or the extraction of NE relations (NERelX), one of the most widely studied areas in information extraction as they are useful for several NLP applications (information retrieval, question-answering, machine translation, summarisation, etc.).

NEs include proper nouns but also entities expressed through other nominal expressions, such as multi-word units, classified into types which may be coarse or fine-grained according to domain or user requirements. Despite years of research, NER still includes several challenges, such as correct classification, resolution of ambiguity, synonym detection, coreference and variability (e.g., acronyms, orthography). Several methods have been used to improve the prediction of correct classes, ranging from rule-based and dictionary-based approaches, to semi-supervised, and unsupervised machine learning techniques. Evaluation depends on the existence of gold (or silver) standards and domain specificity (e.g. genes, proteins, symptoms in health records, etc). Evaluation of NREelX is even more complex when considered in the end-to-end case. How can we evaluate NERelX while taking into account the errors coming from previous analysis steps?

We invite submissions on all topics relating to NE, NER and NE relation extraction, including:

- Definition and typology of NEs, multi-word units

- Domain and document adaptation methods in NER (abstracts, full

papers, wikipedia, domain specific documents, new social media like

twitter, online threads, spoken documents, etc.)

- Detecting NE spans and structural analysis of NEs (NE parsing)

- Cross-document coreference and entity linking

- NE Tracking through time, social or geographical groups, intra- and

inter-document NE tracking etc.

- Normalisation aspects of NE (coreference, disambiguation)

- Recognising NEs in general language and special domains

- Guidelines and annotation tools of NE resources, NE corpora

- Cross-language aspects in NE extraction

- Evaluation, comparison and critical assessment of tools

- NE and NLP applications dependant or based on NEs

LANGUAGE

Manuscripts may be submitted in English or French. French-speaking authors are requested to submit their contributions in French.

THE JOURNAL

TAL (Traitement Automatique des Langues / Natural Language Processing) is an international journal published by ATALA (French Association for Natural Language Processing, http://www.atala.org) since 1959 with the support of CNRS (National Centre for Scientific Research). It has moved to an electronic mode of publication, with printing on demand. http://www.atala.org/-Revue-TAL-

IMPORTANT DATES

April 15, 2013 Deadline for submissions

July 2013 Notification to authors

Autumn 2013 Publication

PAPER SUBMISSION

Papers must describe original, completed, and unpublished work. Each submission will be reviewed by two programme committee members. Authors who intend to submit a paper are encouraged to contact the guest editors of the special issue, with a one page extended abstract. Papers (25 pages, PDF format) must be submitted on Sciencesconf platform [address available soon] FORMAT

Accepted papers will be maximum 25 pages long in PDF. Style sheets are available for download on the Web site of the journal (http://www.atala.org/-Revue-TAL-)

PC members (tentative)

Maud Ehrmann, European Commission, JRC Olivier Galibert, LNE, France Natalia Grabar, STL, Université de Lille 1 et 3, France Kais Haddar, University of Sfax, Tunisie Thierry Hamon, LIM&Bio, Paris 13, France Sanda Harabagiu, Texas, USA Valia Kordoni, Humboldt-Universität, Berlin, Germany Anna Korhonen, University of Cambridge, UK Ioannis Korkontzelos, University of Manchester, UK Anne-Laure Ligozat, LIMSI, France Bernardo Magnini, FBK, HLT, Italy Makoto Miwa, University of Manchester, UK Claire Nedellec, MIG, INRA, France Aurélie Névéol, LIMSI, France Noaoaki Okazaki, University of Manchester, UK Christian Raymond, IRISA, France Fabio Rinaldi, University of Zurich Patrick Ruch, University of Geneva, Swiss Benoit Sagot, ALPAGE, France Satoshi Sekine, NYU, USA Jian Su, A-STAR, Singapore Junichi Tsujii, Microsoft Research Asia, China Patrick Watrin, UCL, CENTAL, Belgique Fabio Zanzotto, Universy of Rome

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