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Introduction
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In the last ten years distributional semantic models (DSMs), such as
LSA, HAL, etc. have been quite successful at addressing semantic
similarity, lexical ambiguity, lexical entailment, verb selectional
restrictions and other word level relations. In this class of models
the meaning of a content word is represented in terms of a distributed
vector recording its pattern of cooccurrences (sometimes, in specific
syntactic relations) with other content words within a
corpus. Different types of semantic tasks and phenomena are then
modeled in terms of linear algebra operations on distributional
vectors.
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A central question about DSMs is whether and how distributional
vectors can also be used in the compositional construction of meaning
for constituents larger than words, and ultimately for sentences or
discourses -- the traditional domains of denotation-based formal
semantics. Being able to model key aspects of semantic composition
represents a crucial condition for DSMs to provide a more general
model of meaning. Conversely, distributional representations might
help to model those aspects of meaning that notoriously challenge
semantic compositionality, such as semantic context-sensitivity,
polysemy, predicate coercion, etc.
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The workshop aims to bring together researchers in formal
and computational semantics to chart this largely unexplored
territory. Some questions to be addressed:
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- Is it possible, and useful, to use Distributional Semantic Models to
assign a semantic representation to constituents (e.g. phrases,
propositions, etc.)?
- How can the notion of predication be interpreted in Distributional
Semantic Models?
- Can Distributional Semantic Models provide an alternative way to
solve puzzles concerning predicate-argument composition
(e.g. type-mismatch, coercion, etc.)?
- Can we use distributional models to capture argument structure and
its alternations, or the Aktionsart of a complex predicates?
- Can distributional semantic models apply below the word level,
characterizing the notions of morpheme productivity and morpheme
composition? (e.g. can we capture distributionally the decreasingly
compositional meanings of "inter+breed", "inter+act", "inter+view"?)
- Can distributional semantic models be used to model word meaning
interactions in modificational contexts, such as figurative
interpretations, context-sensitive sense shifts (e.g. "fast car"
vs. "fast guitarist"), etc.?
- How can polysemy and ambiguity be modelled in distributional
semantic models? Which types of ambiguity could be resolved in a
DSM-based compositional process? Can this help the task of
resolving lexical and textual entailments?
- What is the right relation between the interpretation functions of
formal semantics and the distributional semantic representation
these models provide?
- What should be the most insightful relation between distributional
semantic representations of content words and the meaning of the
function words that combine with them?
- Can DSMs provide distributional correlates of constructions and
lexical classes that are known to be relevant in formal semantics?
(e.g. distributional models of bare plurals, the count vs. mass
distinction, generic vs. episodic predicates, etc.).
- Similarly, can these models capture different types of reference
(e.g. nouns or noun phrases that refer to objects, to kinds, to
events, to facts or propositions, etc.).
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Contacts
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Alessandro Lenci, Department of Linguistics
University of Pisa, Via Santa Maria 36
56126 PISA Italia
Fax: +39 050 2215646
Phone: +39 050 2215638
Mail: alessandro.lenci@ling.unipi.it
Web: http://www.humnet.unipi.it/linguistica/Docenti/Lenci/index.htm
Roberto Zamparelli
Center for Mind/Brain Sciences (CIMeC)
University of Trento, Palazzo Fedrigotti, Corso Bettini, 31
38068 Rovereto (TN), ITALY
Fax: +39 0464 808654
Phone: +39 0464 80 8613
Mail: roberto.zamparelli@unitn.it
Web: http://portale.unitn.it/cimec/persone/roberto.zamparelli
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