Shalom Lappin
Abstracts and Files of Recent Papers
Machine Learning as a Source of Insight into Universal Grammar
Shalom Lappin
Stuart Shieber
Department of
Philosophy
Division
of Engineering and Applied Science
King's
College, London
Harvard
University
shalom.lappin@kcl.ac.uk shieber@deas.harvard.edu
and
Michael Collins
Computer Science
and Artificial Intelligence Laboratory
MIT
mcollins@csail.mit.edu
It is
widely believed that the scientific enterprise
of theoretical linguistics and the engineering of language applications are
separate endeavors with little for their techniques and results to
contribute to each other at the moment. In this paper, we explore
the
possibility that machine learning approaches to natural-language processing
(NLP) being developed in engineering-oriented
computational linguistics (CL) may be able to provide specific scientific insights
into the nature of human language. We argue
that, in
principle, machine learning (ML) results could inform basic debates about
language in one area at least, language acquisition,
and that,
in practice, existing results may offer initial tentative support for this
prospect.
Download
the pdf file
In H. Bunt and R. Muskes (eds.), Computing Meaning Vol. 3, Springer,
2006.
SHARDS: Fragment Resolution in Dialogue
Raquel Fernandez1, Jonathan Ginzburg2,
Howard Gregory3, and Shalom Lappin4
1Institut für Linguistik
Universität
Karl-Liebknecht-Str. 24-25D-14476 Golm
raquel@ling.uni-potsdam.de
2Dept. of Computer
Science
King's College, London
The Strand,
UK
jonathan.ginzburg@kcl.ac.uk
3Seminar fuer Englische Sprachwissenschaft
Georg-August-Universitaet Goettingen
howard.gregory@phil.uni-goettingen.de
4Dept. of Philosophy
King's College, London
The Strand,
UK
shalom.lappin@kcl.ac.uk
October, 2006
In this paper we present
the main features of SHARDS - a Semantically-based HPSG Approach to the
Resolution of Dialogue fragments. This implemented system interprets short
questions (sluices) and short answers. It provides a procedure for computing
the content values of clausal fragments from contextual information contained
in a discourse record of previously
processed sentences.
Download the pdf file
In Proceedings of The Fifteenth
Achieving
Expressive Completeness and Computational Efficiency
for Underspecified Semantic Representations
Chris
Fox
Shalom Lappin
Department of Computer Science
Department of Philosophy
University of Essex
King's
College, London
foxcj@essex.ac.uk
November, 2005
The tension between expressive power and computational tractability
poses an acute problem for theories of underspecified
semantic representation. In previous
work we have presented an account of underspecified scope representations
within Property
Theory with Curry Typing (PTCT), an intensional first-order theory for natural language
semantics. Here we show how filters
applied to the underspecified scope
terms of PTCT permit both expressive completeness and the reduction of
computational
complexity in a significant class of
non-worst case scenarios.
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the pdf file
To appear in Proceedings
of CLIN 2004,
Machine Learning and the Cognitive Basis of Natural Language
Shalom Lappin
Deptartment of Computer Science
King's College, London
July, 2005
Machine learning and statistical methods have yielded impressive results in a wide
variety of natural language processing
tasks. These advances have
generally been regarded as engineering achievements. In fact it is possible to
argue that the success
of machine learning methods is significant for our
understanding of the cognitive basis of language acquisition and processing.
Recent work in unsupervised grammar induction is particularly relevant
to this issue. It suggests that knowledge of language
can be achieved through general learning procedures, and
that a richly
articulated language faculty is not required to explain its
acquisition .
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the pdf file
In Proceedings of SIGdial 6, Lisbon, 2005, pp. 77-86.
Using Machine Learning for Non-Sentential Utterance Classification
Raquel Fernandez,
Jonathan Ginzburg, and Shalom Lappin
Dept. of Computer Science
King's College,
{raquel,ginzburg,lappin}@dcs.kcl.ac.uk
July,
2005
In this
paper we investigate the use of machine learning techniques to classify a wide
range of non-sentential utterance types in dialogue,
a necessary first step in the interpretation of such
fragments. We train different learners on a set of contextual features that can
be extracted
from PoS information. Our results achieve an 87\% weighted
f-score---a 25% improvement over a simple rule-based algorithm baseline.
Download the pdf file
In the Journal
of Logic and Computation 15, 2005, pp. 129-141.
Underspecified Interpretations in a Curry-Typed Representation Language
Chris
Fox
Shalom Lappin
Department of Computer Science
Department of Computer Science
University of Essex
King's
College,
foxcj@essex.ac.uk
April, 2005
In previous work we have developed Property Theory with Curry Typing
(PTCT), an intensional
first-order logic for natural language
semantics. PTCT permits
fine-grained specifications of meaning. It also supports polymorphic types and
separation types. Here we extend
the type system to include product types, and use these
to define a permutation function that generates underspecified scope
representations
within
PTCT. We indicate how filters can be added to encode constraints on possible
scope readings. Our account offers several important
advantages
over other current theories of underspecification.
Download
the pdf file
In Proceedings of the IWCS-6,
Automatic Bare
Sluice Disambiguation in Dialogue
Raquel Fernandez, Jonathan Ginzburg, and
Shalom Lappin
Dept. of Computer Science
King's
College,
{raquel,ginzburg,lappin}@dcs.kcl.ac.uk
January, 2005
The capacity to recognize
and interpret sluices (bare wh-phrases that
exhibit a sentential meaning) is essential to maintaining cohesive interaction
between human users and a machine interlocutor in a dialogue system. In this
paper we present a machine learning approach to sluice disambiguation
in dialogue. Our experiments, based on solid theoretical considerations, show
that applying machine learning techniques using a compact set of
features that can be automatically identified
from PoS labelling in a corpus can be an efficient
tool for disambiguating among possible sluice
interpretations.
Download the pdf file
In Proceedings of COLING 2004,
Classifying
Ellipsis in Dialogue: A Machine Learning Approach
Raquel Fernandez,
Jonathan Ginzburg, and Shalom Lappin
Dept. of
Computer Science
King's College,
{raquel,ginzburg,lappin}@dcs.kcl.ac.uk
June, 2004
We present Property Theory
with Curry Typing (PTCT), an intensional
first-order logic for natural language semantics. PTCT permits fine-grained
specifications of meaning. It also supports polymorphic types and separation
types. We develop an intensional number theory within
PTCT in order
to represent proportional generalized quantifiers like most. We use the
type system and our treatment of generalized quantifiers in natural language
to construct a type-theoretic approach to pronominal anaphora that avoids some
of the difficulties that undermine previous type-theoretic analyses
of this phenomenon.
Download the
pdf file
In the Logic Journal of the International Group for Pure and Applied
Logic 12, 2004, pp. 135-168.
An Expressive First-Order Logic with Flexible Typing for
Natural Language Semantics
Chris
Fox
Shalom Lappin
Department of Computer
Science
Department of Computer Science
University of Essex
King's
College,
foxcj@essex.ac.uk
April, 2004
We present Property Theory with Curry Typing (PTCT),
an intensional first-order logic for natural language
semantics. PTCT permits fine-grained
specifications of meaning. It also supports polymorphic types and separation
types. We develop an intensional number theory within
PTCT in order
to represent proportional generalized quantifiers like most. We use the
type system and our treatment of generalized quantifiers in natural language
to construct a type-theoretic approach to pronominal anaphora that avoids some
of the difficulties that undermine previous type-theoretic analyses of
this phenomenon.
Download the pdf file
In
N. Nicolov, R. Mitkov, G. Angelova, and K. Botcheva
(eds.), Recent Advances in Natural Language Processing III:
Selected
Papers from RANLP 2003, John Benjamins,
Amsterdam, 2004, pp. 1-16.
.
A
Type-Theoretic Approach to Anaphora and Ellipsis
Chris
Fox
Shalom Lappin
Department of Computer Science
Department of Computer Science
University of Essex
King's
College,
foxcj@essex.ac.uk
May, 2004
We present an approach to
anaphora and ellipsis resolution in which pronouns and elided structures are
interpreted by the dynamic identification in
discourse of type constraints on their semantic representations. The content of
these conditions is recovered in context from an antecedent expression.
The constraints define separation types (sub-types) in Property Theory with
Curry Typing (PTCT), an expressive first-order logic
with Curry typing
that we have proposed as a formal framework for natural language semantics.
Download the pdf file
In G. Jaeger, P. Monachesi, G. Penn, and S. Wintner
(eds.), Proceedings of Formal Grammar 2003, Vienna, pp. 89-102.
Doing
Natural Language Semantics in an Expressive
First-Order Logic
with
Flexible Typing
Chris
Fox
Shalom Lappin
Department of Computer
Science
Department of Computer Science
University of Essex
King's
College,
foxcj@essex.ac.uk
May, 2003
We present Property Theory
with Curry Typing (PTCT), an intensional first-order logic for natural language semantics.
PTCT permits
fine-grained specifications of meaning. It also supports polymorphic types and separation types (separation types are also
known as sub-types).
We develop an intensional number theory within PTCT in order to represent proportional
generalized quantifiers like most. We use the
type system and our treatment of generalized quantifiers in natural language to
construct a type-theoretic approach to pronominal anaphora that
avoids some of the difficulties that undermine previous type-theoretic analyses
of this phenomenon.
Download the ps file
Download the pdf file
In A. Branco, A, McEnery, and R. Mitkov (eds.), Anaphora
Processing: Linguistic, Cognitive, and Computational
Modelling, John Benjamins,
A Sequenced Model of Anaphora and Ellipsis Resolution
Shalom Lappin
Dept.
of Computer Science
King's
College,
June,
2003
I compare several types of
knowledge-based and knowledge-poor approaches to anaphora and ellipsis
resolution. The former are able to
capture fine-grained distinctions that depend on lexical meaning and real world
knowledge, but they are generally not robust. The latter
show considerable promise for yielding wide coverage systems. However,
they consistently miss a small but significant subset of cases that
are not accessible to rough-grained techniques of intepretation.
I propose a sequenced model which first applies the most computationally
efficient and inexpensive methods to resolution and then progresses
successively to more costly techniques to deal with cases not handled
by previous modules. Confidence measures evaluate the judgements of each
component in order to determine which instances of anaphora
or ellipsis are to be passed on to the next, more
fine-grained subsystem.
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Download the pdf file
In G. Alberti,
K. Balough, and P. Dekker
(eds.), Proceedings of the Seventh Symposium for Logic and Language, Pecs, Hungary, 2002, pp.37-46.
A Higher-Order Fine-Grained Logic for Intensional
Semantics
Chris
Fox
Shalom Lappin
Department of Computer
Science
Department of Computer Science
University of Essex
King's
College, London
foxcj@essex.ac.uk
and
Carl Pollard
Department of Linguistics
Ohio
State University
pollard@ling.ohio-state.edu
June, 2002
This paper describes a
higher-order logic with fine-grained intensionality (FIL). Unlike traditional Montogovian type theory,
intensionality is treated as basic, rather than
derived through possible worlds. This allows for fine-grained intensionality without
impossible worlds. Possible worlds and modalities are defined algebraically.
The proof theory for \FIL is given as a set of
tableau rules, and an algebraic model theory is specified. The proof
theory is shown to be sound relative to this model theory.
FIL avoids many of the problems created by classical course-grained intensional logics that have been used in formal and
computational semantics.
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Download the pdf file
In G. Alberti, K. Balough, and P. Dekker (eds.), Proceedings
of the Seventh Symposium for Logic and Language, Pecs,
Hungary, 2002, pp. 47-56.
Intensional First-Order Logic with Types
Chris Fox
Shalom Lappin
Department of Computer Science Department
Computer Science
University
of
Essex
King's College, London
foxcj@essex.ac.uk
and
Carl Pollard
Department of Linguistics
Ohio State University
pollard@ling.ohio-state.edu
June, 2002
The paper presents Property
Theory with Curry Typing (PTCT) where the language of terms and well-formed
formulae are
joined by a language of types. In addition to
supporting fine-grained intensionality,
the basic theory is essentially first-order,
so that implementations using the theory can apply standard first-order theorem
proving techniques. Some extensions to the
type theory are discussed, type polymorphism, and enriching the system with sufficient
number theory to account for
quantifiers of proportion, such as most.
Download the ps file
Download the pdf file
In
First-Order Curry-Typed Logic for Natural
Language
Semantics
Chris
Fox
Shalom Lappin
Department of Computer Science Department
Computer Science
University
of
Essex
King's College, London
foxcj@essex.ac.uk
and
Carl Pollard
Department of Linguistics
Ohio State University
pollard@ling.ohio-state.edu
May, 2002
The paper presents Property
Theory with Curry Typing (PTCT) where the language of terms and well-formed
formulae are joined by a language of types. In
addition to supporting fine-grained intensionality,
the basic theory is essentially first-order, so that implementations using the
theory can apply standard first-order theorem proving techniques. The paper
sketches a system of tableau rules that implements the theory. Some extensions
to the type theory are discussed, including the possibility of adding type
polymorphism, which provides a useful analysis of conjunctive terms. Such terms
can be given a single polymorphic type that expresses the fact that they can
conjoin phrases of any one type, yielding an expression of the same type.
Download the ps file
Download the pdf file
An updated version of a paper in P. de Groote,
G. Morrill, and C. Retore (eds.) (2001), Logical
Aspects of Computational Linguistics, Springer
Lecture Notes in Artificial Intelligence, Berlin and New York.
A Framework for the Hyperintensional
Semantics of Natural Language with Two Implementations
Chris
Fox and Shalom Lappin
Dept.
of Computer Science
King's College,
London
The
Strand, London WC2R 2LS
United Kingdom
{foxcj,lappin}@dcs.kcl.ac.uk
April, 2001
In this paper we present a
framework for constructing hyperintensional semantics
for natural language. On this approach, the axiom of extensionality is
discarded from the axiom base of a logic. Weaker
conditions are specified for the connection between equivalence and identity
which prevent the reduction of the former relation to the latter. In addition,
by axiomatising
an intensional number theory we can provide an
internal account of proportional cardinality quantifiers, like most. We
use a (pre-)lattice defined in terms of a (pre-)order
that models the entailment relation. Possible worlds/situations/indices are
then prime filters of propositions in the (pre-)lattice.
Truth in a world/situation is then reducible to membership of a prime filter.
We show how this approach can be implemented within (i)
an intensional higher-order
type theory, and (ii) first-order property theory.
Download
the ps file (Copyright Springer-Verlag)
in J. van Kuppevelt and
R. Smith (eds.) (2003), Current and NewDirections
in Discourse and Dialogue, Kluwer, pp.161-181.
Full Paraphrase Generation for Fragments in
Dialogue
Christian Ebert, Shalom Lappin,
Department
of Computer Science
King's
College,
{ebert, lappin}@dcs.kcl.ac.uk},{howard.gregory@kcl.ac.uk}
Howard Gregory
Seminar
fuer Englische Sprachwissenschaft
Georg-August-Universitaet Goettingen
howard.gregory@phil.uni-goettingen.de
and
nicolas@us.ibm.com
July, 2002
Using SHARDS -- a
semantically-based HPSG resolution of dialogue fragment system -- we will show
how to generate full paraphrases for fragments in dialogue. We adopt a
template-filler approach that does not require deep generation from an
underlying semantic representation. Instead it reuses the results of the parse
and interpretation process to dynamically compute templates and to update
fillers as the dialogue proceeds. This recycling of already available syntactic
and phonological information makes generation efficient, as it reduces the
operations of the generator to mere string manipulations.