Annie Zaenen,
Bonnie Webber,
University of Edinburgh, UK
Martha Palmer,
University of Colorado, USA
Editorial Board
Jason Baldridge,
UT, Austin, USA
Johan Bos,
University of Rome, Italy
Gosse Bouma,
University of Groningen,
The Netherlands
John Carroll,
University of Sussex, UK
Robin Cooper,
Göteborg University, Sweden
Ann Copestake,
University of Cambridge, UK
Robert Dale,
Macquarie University, Australia
Jason Eisner,
Johns Hopkins University, USA
Elisabet Engdahl,
Göteborg University, Sweden
Dan Flickinger,
Stanford University, USA
Anette Frank,
University of Heidelberg, Germany
John Goldsmith,
The University of Chicago, USA
Mary Harper,
Purdue University, USA
Chu-Ren Huang,
Academia Sinica, Taiwan
Mark Johnson,
Brown University, USA
Aravind Joshi,
UPenn, USA
Ron Kaplan,
PowerSet, USA
Martin Kay,
Stanford University, USA
Lori Lamel,
LIMSI, France
Roger Levy,
Mark Liberman,
UPenn, USA
Christopher Manning,
Stanford University, USA
Detmar Meurers,
The Ohio State University, USA
Gertjan van Noord,
University of Groningen,
The Netherlands
Kemal Oflazer,
Sabancı University, Turkey
Janet Pierrehumbert,
Northwestern University, USA
Livia Polanyi,
PowerSet, USA
Stephen Pulman,
Oxford University, UK
Philip Resnik,
University of Maryland, USA
Hinrich Schütze,
University of Stuttgart, Germany
Mark Steedman,
University of Edinburgh, UK
Matthew Stone,
Rutgers University, USA
Jun’ichi Tsujii,
University of Tokyo, Japan


Linguistic Issues in Language Technology (LiLT) is a new open-access journal that focusses on relationships between linguistic insights, which can prove valuable to language technology, and language technology, which can enrich linguistic research.

The Editorial Board of LiLT believes that, in conjunction with machine learning and statistical techniques, deeper and more sophisticated models of language are needed to make significant progress in newly emerging areas of computational language analysis. LiLT provides a forum for such work. LiLT takes an eclectic view on methodology.

LiLT accepts short research notes (< 4 pages), squibs (<8 pages) and full fledged articles (no page limit). We will review research notes within 3-4 weeks, squibs within 6 weeks and full fledged papers within 2 months. Articles will be published as soon as they are in their final state. The on-line version is free of charge. Once a year the contributions will be gathered in a printed volume.

Submissions should be sent electronically to Annie Zaenen
and follow the LiLT style sheet (see LiLT Style)
Final submissions should be submitted in PDF format.

You can find the current issue here.

Issues that fall in the purview of LiLT include but are not limited to:

automatic recognition of entailment; reference resolution procedures; anaphora resolution; formalisms for linguistic context, ellipsis, and coordination in dialogue that interface with implemented approaches to conversational reasoning; parsing models that quantify syntactic and semantic relations; machine-readable resources including lexicons, thesauri and ontologies; annotation schemas for syntactic, semantic and pragmatic phenomena in diverse languages and genres; linguistically informed techniques for error-analysis and performance evaluation; typologically motivated linguistic generalizations and contrastive studies that might inform cross linguistic applications and machine translation; high-level representations for language modeling in ASR; semantic role labeling; building semantic representations; incorporating linguistic information into statistical language models; grammar engineering; applications of formal mathematical models to language technology; use of linguistic information for bootstrapping data collections; use of statistics in rule-based linguistic models; use of linguistic insights in statistical and machine learning modeling of natural language.


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