25.4342, Calls: Computational Linguistics; Semantics/ Computational Linguistics (Jrnl)

Sat Nov 1 16:04:36 UTC 2014

LINGUIST List: Vol-25-4342. Sat Nov 01 2014. ISSN: 1069 - 4875.

Subject: 25.4342, Calls: Computational Linguistics; Semantics/ Computational Linguistics (Jrnl)

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Date: Sat, 01 Nov 2014 12:04:20
From: Aurelie Herbelot [aurelie.herbelot at cantab.net]
Subject: Computational Linguistics; Semantics/ Computational Linguistics (Jrnl)

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Full Title: Computational Linguistics 

Linguistic Field(s): Computational Linguistics; Semantics 

Call Deadline: 01-Apr-2015 

Special Issue of Computational Linguistics: Formal Distributional Semantics

1st Call for Papers

Submission deadline: April 1st 2015

http://www.cl.cam.ac.uk/~ah433/CL-special-issue-formal-distributional-semantic
s.html

The semantics of natural language consists of complex phenomena encompassing
functional aspects such as quantification (e.g. ''the cat'' vs. ''a cat'') and
conceptual aspects related to word meaning (e.g. ''cat'' vs. ''animal'';
''visit Boston'' vs. ''visit a friend''). No existing theory of meaning
accounts for both, and existing approaches are typically biased towards one or
the other. For instance, formal semantics focuses on functional aspects,
providing a systematic treatment of compositionality through a clear
syntax-semantics interface -- at the expense of lexical semantics.
Distributional, or vector-space, semantics (Turney & Pantel, 2010), on the
other hand, excels at lexical semantics phenomena ranging from word similarity
to categorization, and it has recently made progress towards the treatment of
composition (Baroni 2013); however, functional aspects remain mostly
unaccounted for.
Because of the complementary strengths of the two approaches, the
computational linguistics community has started investigating proposals for an
overarching architecture, combining formal and distributional semantics (e.g.
Coecke et al., 2011; Erk, 2013; Lewis and Steedman 2013; Baroni et al., 2014).
This effort holds the promise of significantly advancing the state of the art.
However, given the fundamentally different nature of formal and distributional
semantics, the enterprise also poses great challenges. The aim of this special
issue is to explore the boundaries of a formal distributional semantics, by
proposing relevant computational accounts of meaning and applying the
corresponding frameworks to specific linguistic phenomena.

Topics

For this special issue, we solicit full-length article submissions describing
original research on any aspect of formal distributional semantics integrating
a computational perspective. Possible topics include, but are not limited to:
- Theoretical questions: What is meaning in formal distributional semantics,
and how well do computational models simulate the relevant theories? How can
distributional representations be related to the traditional components of a
semantics for natural languages, especially reference and truth? Is similarity
(the chief notion in distributional semantics) at odds with inference (one of
the testbeds of formal semantics), or can it support it?
- Framework issues: Should a framework be developed that encompasses both
formal and distributional semantics in a single formalism (Baroni et al.,
2014), or should the two approaches be kept separate and linked via systematic
interactions (Lewis and Steedman 2013; Garrette et al., 2014)? How do
different frameworks fare in standard computational semantics benchmarks (RTE,
STS, etc.)? 
- Linguistic phenomena: Can formal distributional semantics account for known
phenomena? Can it shed new light on old puzzles? Can it handle newly observed
phenomena? 

Submission Instructions

Articles submitted to this special issue must adhere to the Computational
Linguistics Style Guidelines. The submission guidelines can be found on the CL
web site (http://cljournal.org/submissions.html). 

Guest Editors
Gemma Boleda
Universitat Pompeu Fabra, Barcelona, Spain
gemma.boleda at upf.edu
Aurelie Herbelot
University of Cambridge, UK
aurelie.herbelot at cantab.net

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