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cmp-lg/9505041
|
On Descriptive Complexity, Language Complexity, and GB
|
cmp-lg cs.CL
|
We introduce $L^2_{K,P}$, a monadic second-order language for reasoning about
trees which characterizes the strongly Context-Free Languages in the sense that
a set of finite trees is definable in $L^2_{K,P}$ iff it is (modulo a
projection) a Local Set---the set of derivation trees generated by a CFG. This
provides a flexible approach to establishing language-theoretic complexity
results for formalisms that are based on systems of well-formedness constraints
on trees. We demonstrate this technique by sketching two such results for
Government and Binding Theory. First, we show that {\em free-indexation\/}, the
mechanism assumed to mediate a variety of agreement and binding relationships
in GB, is not definable in $L^2_{K,P}$ and therefore not enforcible by CFGs.
Second, we show how, in spite of this limitation, a reasonably complete GB
account of English can be defined in $L^2_{K,P}$. Consequently, the language
licensed by that account is strongly context-free. We illustrate some of the
issues involved in establishing this result by looking at the definition, in
$L^2_{K,P}$, of chains. The limitations of this definition provide some insight
into the types of natural linguistic principles that correspond to higher
levels of language complexity. We close with some speculation on the possible
significance of these results for generative linguistics.
|
cmp-lg/9505042
|
Robust Parsing Based on Discourse Information: Completing partial parses
of ill-formed sentences on the basis of discourse information
|
cmp-lg cs.CL
|
In a consistent text, many words and phrases are repeatedly used in more than
one sentence. When an identical phrase (a set of consecutive words) is repeated
in different sentences, the constituent words of those sentences tend to be
associated in identical modification patterns with identical parts of speech
and identical modifiee-modifier relationships. Thus, when a syntactic parser
cannot parse a sentence as a unified structure, parts of speech and
modifiee-modifier relationships among morphologically identical words in
complete parses of other sentences within the same text provide useful
information for obtaining partial parses of the sentence. In this paper, we
describe a method for completing partial parses by maintaining consistency
among morphologically identical words within the same text as regards their
part of speech and their modifiee-modifier relationship. The experimental
results obtained by using this method with technical documents offer good
prospects for improving the accuracy of sentence analysis in a broad-coverage
natural language processing system such as a machine translation system.
|
cmp-lg/9505043
|
Using Decision Trees for Coreference Resolution
|
cmp-lg cs.CL
|
This paper describes RESOLVE, a system that uses decision trees to learn how
to classify coreferent phrases in the domain of business joint ventures. An
experiment is presented in which the performance of RESOLVE is compared to the
performance of a manually engineered set of rules for the same task. The
results show that decision trees achieve higher performance than the rules in
two of three evaluation metrics developed for the coreference task. In addition
to achieving better performance than the rules, RESOLVE provides a framework
that facilitates the exploration of the types of knowledge that are useful for
solving the coreference problem.
|
cmp-lg/9505044
|
Automatic Evaluation and Uniform Filter Cascades for Inducing N-Best
Translation Lexicons
|
cmp-lg cs.CL
|
This paper shows how to induce an N-best translation lexicon from a bilingual
text corpus using statistical properties of the corpus together with four
external knowledge sources. The knowledge sources are cast as filters, so that
any subset of them can be cascaded in a uniform framework. A new objective
evaluation measure is used to compare the quality of lexicons induced with
different filter cascades. The best filter cascades improve lexicon quality by
up to 137% over the plain vanilla statistical method, and approach human
performance. Drastically reducing the size of the training corpus has a much
smaller impact on lexicon quality when these knowledge sources are used. This
makes it practical to train on small hand-built corpora for language pairs
where large bilingual corpora are unavailable. Moreover, three of the four
filters prove useful even when used with large training corpora.
|
cmp-lg/9505045
|
Hybrid Transfer in an English-French Spoken Language Translator
|
cmp-lg cs.CL
|
The paper argues the importance of high-quality translation for spoken
language translation systems. It describes an architecture suitable for rapid
development of high-quality limited-domain translation systems, which has been
implemented within an advanced prototype English to French spoken language
translator. The focus of the paper is the hybrid transfer model which combines
unification-based rules and a set of trainable statistical preferences;
roughly, rules encode domain-independent grammatical information and
preferences encode domain-dependent distributional information. The preferences
are trained from sets of examples produced by the system, which have been
annotated by human judges as correct or incorrect. An experiment is described
in which the model was tested on a 2000 utterance sample of previously unseen
data.
|
cmp-lg/9506001
|
Ma(r)king concessions in English and German
|
cmp-lg cs.CL
|
In order to generate cohesive discourse, many of the relations holding
between text segments need to be signalled to the reader by means of cue words,
or {\em discourse markers}. Programs usually do this in a simplistic way, e.g.,
by using one marker per relation. In reality, however, language offers a very
wide range of markers from which informed choices should be made. In order to
account for the variety and to identify the parameters governing the choices,
detailled linguistic analyses are necessary. We worked with one area of
discourse relations, the Concession family, identified its underlying
pragmatics and semantics, and undertook extensive corpus studies to examine the
range of markers used in both English and German. On the basis of an initial
classification of these markers, we propose a generation model for producing
bilingual text that can incorporate marker choice into its overall decision
framework.
|
cmp-lg/9506002
|
Weak subsumption Constraints for Type Diagnosis: An Incremental
Algorithm
|
cmp-lg cs.CL
|
We introduce constraints necessary for type checking a higher-order
concurrent constraint language, and solve them with an incremental algorithm.
Our constraint system extends rational unification by constraints x$\subseteq$
y saying that ``$x$ has at least the structure of $y$'', modelled by a weak
instance relation between trees. This notion of instance has been carefully
chosen to be weaker than the usual one which renders semi-unification
undecidable. Semi-unification has more than once served to link unification
problems arising from type inference and those considered in computational
linguistics. Just as polymorphic recursion corresponds to subsumption through
the semi-unification problem, our type constraint problem corresponds to weak
subsumption of feature graphs in linguistics. The decidability problem for
\WhatsIt for feature graphs has been settled by
D\"orre~\cite{Doerre:WeakSubsumption:94}. \nocite{RuppRosnerJohnson:94} In
contrast to D\"orre's, our algorithm is fully incremental and does not refer to
finite state automata. Our algorithm also is a lot more flexible. It allows a
number of extensions (records, sorts, disjunctive types, type declarations, and
others) which make it suitable for type inference of a full-fledged programming
language.
|
cmp-lg/9506003
|
Syllable parsing in English and French
|
cmp-lg cs.CL
|
In this paper I argue that Optimality Theory provides for an explanatory
model of syllabic parsing in English and French. The argument is based on
psycholinguistic facts that have been mysterious up to now. This argument is
further buttressed by the computational implementation developed here. This
model is important for several reasons. First, it provides a demonstration of
how OT can be used in a performance domain. Second, it suggests a new
relationship between phonological theory and psycholinguistics. (Code in Perl
is included and a WWW-interface is running at
http://mayo.douglass.arizona.edu.)
|
cmp-lg/9506004
|
Using Higher-Order Logic Programming for Semantic Interpretation of
Coordinate Constructs
|
cmp-lg cs.CL
|
Many theories of semantic interpretation use lambda-term manipulation to
compositionally compute the meaning of a sentence. These theories are usually
implemented in a language such as Prolog that can simulate lambda-term
operations with first-order unification. However, for some interesting cases,
such as a Combinatory Categorial Grammar account of coordination constructs,
this can only be done by obscuring the underlying linguistic theory with the
``tricks'' needed for implementation. This paper shows how the use of abstract
syntax permitted by higher-order logic programming allows an elegant
implementation of the semantics of Combinatory Categorial Grammar, including
its handling of coordination constructs.
|
cmp-lg/9506005
|
A Support Tool for Tagset Mapping
|
cmp-lg cs.CL
|
Many different tagsets are used in existing corpora; these tagsets vary
according to the objectives of specific projects (which may be as far apart as
robust parsing vs. spelling correction). In many situations, however, one would
like to have uniform access to the linguistic information encoded in corpus
annotations without having to know the classification schemes in detail. This
paper describes a tool which maps unstructured morphosyntactic tags to a
constraint-based, typed, configurable specification language, a ``standard
tagset''. The mapping relies on a manually written set of mapping rules, which
is automatically checked for consistency. In certain cases, unsharp mappings
are unavoidable, and noise, i.e. groups of word forms {\sl not} conforming to
the specification, will appear in the output of the mapping. The system
automatically detects such noise and informs the user about it. The tool has
been tested with rules for the UPenn tagset \cite{up} and the SUSANNE tagset
\cite{garside}, in the framework of the EAGLES\footnote{LRE project EAGLES, cf.
\cite{eagles}.} validation phase for standardised tagsets for European
languages.
|
cmp-lg/9506006
|
Automatic Extraction of Tagset Mappings from Parallel-Annotated Corpora
|
cmp-lg cs.CL
|
This paper describes some of the recent work of project AMALGAM (automatic
mapping among lexico-grammatical annotation models). We are investigating ways
to map between the leading corpus annotation schemes in order to improve their
resuability. Collation of all the included corpora into a single large
annotated corpus will provide a more detailed language model to be developed
for tasks such as speech and handwriting recognition. In particular, we focus
here on a method of extracting mappings from corpora that have been annotated
according to more than one annotation scheme.
|
cmp-lg/9506007
|
Features and Agreement
|
cmp-lg cs.CL
|
This paper compares the consistency-based account of agreement phenomena in
`unification-based' grammars with an implication-based account based on a
simple feature extension to Lambek Categorial Grammar (LCG). We show that the
LCG treatment accounts for constructions that have been recognized as
problematic for `unification-based' treatments.
|
cmp-lg/9506008
|
CLiFF Notes: Research in the Language, Information and Computation
Laboratory of the University of Pennsylvania
|
cmp-lg cs.CL
|
Short abstracts by computational linguistics researchers at the University of
Pennsylvania describing ongoing individual and joint projects.
|
cmp-lg/9506009
|
Filling Knowledge Gaps in a Broad-Coverage Machine Translation System
|
cmp-lg cs.CL
|
Knowledge-based machine translation (KBMT) techniques yield high quality in
domains with detailed semantic models, limited vocabulary, and controlled input
grammar. Scaling up along these dimensions means acquiring large knowledge
resources. It also means behaving reasonably when definitive knowledge is not
yet available. This paper describes how we can fill various KBMT knowledge
gaps, often using robust statistical techniques. We describe quantitative and
qualitative results from JAPANGLOSS, a broad-coverage Japanese-English MT
system.
|
cmp-lg/9506010
|
Two-level, Many-Paths Generation
|
cmp-lg cs.CL
|
Large-scale natural language generation requires the integration of vast
amounts of knowledge: lexical, grammatical, and conceptual. A robust generator
must be able to operate well even when pieces of knowledge are missing. It must
also be robust against incomplete or inaccurate inputs. To attack these
problems, we have built a hybrid generator, in which gaps in symbolic knowledge
are filled by statistical methods. We describe algorithms and show experimental
results. We also discuss how the hybrid generation model can be used to
simplify current generators and enhance their portability, even when perfect
knowledge is in principle obtainable.
|
cmp-lg/9506011
|
Unification-Based Glossing
|
cmp-lg cs.CL
|
We present an approach to syntax-based machine translation that combines
unification-style interpretation with statistical processing. This approach
enables us to translate any Japanese newspaper article into English, with
quality far better than a word-for-word translation. Novel ideas include the
use of feature structures to encode word lattices and the use of unification to
compose and manipulate lattices. Unification also allows us to specify abstract
features that delay target-language synthesis until enough source-language
information is assembled. Our statistical component enables us to search
efficiently among competing translations and locate those with high English
fluency.
|
cmp-lg/9506012
|
Presenting Punctuation
|
cmp-lg cs.CL
|
Until recently, punctuation has received very little attention in the
linguistics and computational linguistics literature. Since the publication of
Nunberg's (1990) monograph on the topic, however, punctuation has seen its
stock begin to rise: spurred in part by Nunberg's ground-breaking work, a
number of valuable inquiries have been subsequently undertaken, including Hovy
and Arens (1991), Dale (1991), Pascual (1993), Jones (1994), and Briscoe
(1994). Continuing this line of research, I investigate in this paper how
Nunberg's approach to presenting punctuation (and other formatting devices)
might be incorporated into NLG systems. Insofar as the present paper focuses on
the proper syntactic treatment of punctuation, it differs from these other
subsequent works in that it is the first to examine this issue from the
generation perspective.
|
cmp-lg/9506013
|
A Study of the Context(s) in a Specific Type of Texts: Car Accident
Reports
|
cmp-lg cs.CL
|
This paper addresses the issue of defining context, and more specifically the
different contexts needed for understanding a particular type of texts. The
corpus chosen is homogeneous and allows us to determine characteristic
properties of the texts from which certain inferences can be drawn by the
reader. These characteristic properties come from the real world domain
(K-context), the type of events the texts describe (F-context) and the genre of
the texts (E-context). Together, these three contexts provide elements for the
resolution of anaphoric expressions and for several types of disambiguation. We
show in particular that the argumentation aspect of these texts is an essential
part of the context and explains some of the inferences that can be drawn.
|
cmp-lg/9506014
|
Inducing Features of Random Fields
|
cmp-lg cs.CL
|
We present a technique for constructing random fields from a set of training
samples. The learning paradigm builds increasingly complex fields by allowing
potential functions, or features, that are supported by increasingly large
subgraphs. Each feature has a weight that is trained by minimizing the
Kullback-Leibler divergence between the model and the empirical distribution of
the training data. A greedy algorithm determines how features are incrementally
added to the field and an iterative scaling algorithm is used to estimate the
optimal values of the weights.
The statistical modeling techniques introduced in this paper differ from
those common to much of the natural language processing literature since there
is no probabilistic finite state or push-down automaton on which the model is
built. Our approach also differs from the techniques common to the computer
vision literature in that the underlying random fields are non-Markovian and
have a large number of parameters that must be estimated. Relations to other
learning approaches including decision trees and Boltzmann machines are given.
As a demonstration of the method, we describe its application to the problem of
automatic word classification in natural language processing.
Key words: random field, Kullback-Leibler divergence, iterative scaling,
divergence geometry, maximum entropy, EM algorithm, statistical learning,
clustering, word morphology, natural language processing
|
cmp-lg/9506015
|
Ambiguity in the Acquisition of Lexical Information
|
cmp-lg cs.CL
|
This paper describes an approach to the automatic identification of lexical
information in on-line dictionaries. This approach uses bootstrapping
techniques, specifically so that ambiguity in the dictionary text can be
treated properly. This approach consists of processing an on-line dictionary
multiple times, each time refining the lexical information previously acquired
and identifying new lexical information. The strength of this approach is that
lexical information can be acquired from definitions which are syntactically
ambiguous, given that information acquired during the first pass can be used to
improve the syntactic analysis of definitions in subsequent passes. In the
context of a lexical knowledge base, the types of lexical information that need
to be represented cannot be viewed as a fixed set, but rather as a set that
will change given the resources of the lexical knowledge base and the
requirements of analysis systems which access it.
|
cmp-lg/9506016
|
Indefeasible Semantics and Defeasible Pragmatics
|
cmp-lg cs.CL
|
An account of utterance interpretation in discourse needs to face the issue
of how the discourse context controls the space of interacting preferences.
Assuming a discourse processing architecture that distinguishes the grammar and
pragmatics subsystems in terms of monotonic and nonmonotonic inferences, I will
discuss how independently motivated default preferences interact in the
interpretation of intersentential pronominal anaphora. In the framework of a
general discourse processing model that integrates both the grammar and
pragmatics subsystems, I will propose a fine structure of the preferential
interpretation in pragmatics in terms of defeasible rule interactions. The
pronoun interpretation preferences that serve as the empirical ground draw from
the survey data specifically obtained for the present purpose.
|
cmp-lg/9506017
|
The Effect of Pitch Accenting on Pronoun Referent Resolution
|
cmp-lg cs.CL
|
By strictest interpretation, theories of both centering and intonational
meaning fail to predict the existence of pitch accented pronominals. Yet they
occur felicitously in spoken discourse. To explain this, I emphasize the dual
functions served by pitch accents, as markers of both propositional
(semantic/pragmatic) and attentional salience. This distinction underlies my
proposals about the attentional consequences of pitch accents when applied to
pronominals, in particular, that while most pitch accents may weaken or
reinforce a cospecifier's status as the center of attention, a contrastively
stressed pronominal may force a shift, even when contraindicated by textual
features.
|
cmp-lg/9506018
|
Intelligent Voice Prosthesis: Converting Icons into Natural Language
Sentences
|
cmp-lg cs.CL
|
The Intelligent Voice Prosthesis is a communication tool which reconstructs
the meaning of an ill-structured sequence of icons or symbols, and expresses
this meaning into sentences of a Natural Language (French). It has been
developed for the use of people who cannot express themselves orally in natural
language, and further, who are not able to comply to grammatical rules such as
those of natural language. We describe how available corpora of iconic
communication by children with Cerebral Palsy has led us to implement a simple
and relevant semantic description of the symbol lexicon. We then show how a
unification-based, bottom-up semantic analysis allows the system to uncover the
meaning of the user's utterances by computing proper dependencies between the
symbols. The result of the analysis is then passed to a lexicalization module
which chooses the right words of natural language to use, and builds a
linguistic semantic network. This semantic network is then generated into
French sentences via hierarchization into trees, using a lexicalized Tree
Adjoining Grammar. Finally we describe the modular, customizable interface
which has been developed for this system.
|
cmp-lg/9506019
|
Review of Charniak's "Statistical Language Learning"
|
cmp-lg cs.CL
|
This article is an in-depth review of Eugene Charniak's book, "Statistical
Language Learning". The review evaluates the appropriateness of the book as an
introductory text for statistical language learning for a variety of audiences.
It also includes an extensive bibliography of articles and papers which might
be used as a supplement to this book for learning or teaching statistical
language modeling.
|
cmp-lg/9506020
|
GLR-Parsing of Word Lattices Using a Beam Search Method
|
cmp-lg cs.CL
|
This paper presents an approach that allows the efficient integration of
speech recognition and language understanding using Tomita's generalized
LR-parsing algorithm. For this purpose the GLRP-algorithm is revised so that an
agenda mechanism can be used to control the flow of computation of the parsing
process. This new approach is used to integrate speech recognition and speech
understanding incrementally with a beam search method. These considerations
have been implemented and tested on ten word lattices.
|
cmp-lg/9506021
|
Prepositional Phrase Attachment through a Backed-Off Model
|
cmp-lg cs.CL
|
Recent work has considered corpus-based or statistical approaches to the
problem of prepositional phrase attachment ambiguity. Typically, ambiguous verb
phrases of the form {v np1 p np2} are resolved through a model which considers
values of the four head words (v, n1, p and n2). This paper shows that the
problem is analogous to n-gram language models in speech recognition, and that
one of the most common methods for language modeling, the backed-off estimate,
is applicable. Results on Wall Street Journal data of 84.5% accuracy are
obtained using this method. A surprising result is the importance of low-count
events - ignoring events which occur less than 5 times in training data reduces
performance to 81.6%.
|
cmp-lg/9506022
|
Deriving Procedural and Warning Instructions from Device and Environment
Models
|
cmp-lg cs.CL
|
This study is centred on the generation of instructions for household
appliances. We show how knowledge about a device, together with knowledge about
the environment, can be used for reasoning about instructions. The information
communicated by the instructions can be planned from a version of the knowledge
of the artifact and environment. We present the latter, which we call the {\it
planning knowledge}, in the form of axioms in the {\it situation calculus}.
This planning knowledge formally characterizes the behaviour of the artifact,
and it is used to produce a basic plan of actions that the device and user take
to accomplish a given goal. We explain how both procedural and warning
instructions can be generated from this basic plan.
In order to partially justify that instruction generation can be automated
from a formal device design specification, we assume that the planning
knowledge is {\it derivable\/} from the device and world knowledge.
|
cmp-lg/9506023
|
Empirical Discovery in Linguistics
|
cmp-lg cs.CL
|
A discovery system for detecting correspondences in data is described, based
on the familiar induction methods of J. S. Mill. Given a set of observations,
the system induces the ``causally'' related facts in these observations. Its
application to empirical linguistic discovery is described.
|
cmp-lg/9506024
|
An Approach to Proper Name Tagging for German
|
cmp-lg cs.CL
|
This paper presents an incremental method for the tagging of proper names in
German newspaper texts. The tagging is performed by the analysis of the
syntactic and textual contexts of proper names together with a morphological
analysis. The proper names selected by this process supply new contexts which
can be used for finding new proper names, and so on. This procedure was applied
to a small German corpus (50,000 words) and correctly disambiguated 65% of the
capitalized words, which should improve when it is applied to a very large
corpus.
|
cmp-lg/9506025
|
A Categorial Framework for Composition in Multiple Linguistic Domains
|
cmp-lg cs.CL
|
This paper describes a computational framework for a grammar architecture in
which different linguistic domains such as morphology, syntax, and semantics
are treated not as separate components but compositional domains. Word and
phrase formation are modeled as uniform processes contributing to the
derivation of the semantic form. The morpheme, as well as the lexeme, has
lexical representation in the form of semantic content, tactical constraints,
and phonological realization. The motivation for this work is to handle
morphology-syntax interaction (e.g., valency change in causatives,
subcategorization imposed by case-marking affixes) in an incremental way. The
model is based on Combinatory Categorial Grammars.
|
cmp-lg/9506026
|
A Computational Approach to Aspectual Composition
|
cmp-lg cs.CL
|
In this paper, I argue, contrary to the prevailing opinion in the linguistics
and philosophy literature, that a sortal approach to aspectual composition can
indeed be explanatory. In support of this view, I develop a synthesis of
competing proposals by Hinrichs, Krifka and Jackendoff which takes Jackendoff's
cross-cutting sortal distinctions as its point of departure. To show that the
account is well-suited for computational purposes, I also sketch an implemented
calculus of eventualities which yields many of the desired inferences. Further
details on both the model-theoretic semantics and the implementation can be
found in (White, 1994).
|
cmp-lg/9507001
|
Constraint Categorial Grammars
|
cmp-lg cs.CL
|
Although unification can be used to implement a weak form of
$\beta$-reduction, several linguistic phenomena are better handled by using
some form of $\lambda$-calculus. In this paper we present a higher order
feature description calculus based on a typed $\lambda$-calculus. We show how
the techniques used in \CLG for resolving complex feature constraints can be
efficiently extended. \CCLG is a simple formalism, based on categorial
grammars, designed to test the practical feasibility of such a calculus.
|
cmp-lg/9507002
|
A framework for lexical representation
|
cmp-lg cs.CL
|
In this paper we present a unification-based lexical platform designed for
highly inflected languages (like Roman ones). A formalism is proposed for
encoding a lemma-based lexical source, well suited for linguistic
generalizations. From this source, we automatically generate an allomorph
indexed dictionary, adequate for efficient processing. A set of software tools
have been implemented around this formalism: access libraries, morphological
processors, etc.
|
cmp-lg/9507003
|
Robust Processing of Natural Language
|
cmp-lg cs.CL
|
Previous approaches to robustness in natural language processing usually
treat deviant input by relaxing grammatical constraints whenever a successful
analysis cannot be provided by ``normal'' means. This schema implies, that
error detection always comes prior to error handling, a behaviour which hardly
can compete with its human model, where many erroneous situations are treated
without even noticing them.
The paper analyses the necessary preconditions for achieving a higher degree
of robustness in natural language processing and suggests a quite different
approach based on a procedure for structural disambiguation. It not only offers
the possibility to cope with robustness issues in a more natural way but
eventually might be suited to accommodate quite different aspects of robust
behaviour within a single framework.
|
cmp-lg/9507004
|
GRAMPAL: A Morphological Processor for Spanish implemented in Prolog
|
cmp-lg cs.CL
|
A model for the full treatment of Spanish inflection for verbs, nouns and
adjectives is presented. This model is based on feature unification and it
relies upon a lexicon of allomorphs both for stems and morphemes. Word forms
are built by the concatenation of allomorphs by means of special contextual
features. We make use of standard Definite Clause Grammars (DCG) included in
most Prolog implementations, instead of the typical finite-state approach. This
allows us to take advantage of the declarativity and bidirectionality of Logic
Programming for NLP.
The most salient feature of this approach is simplicity: A really
straightforward rule and lexical components. We have developed a very simple
model for complex phenomena.
Declarativity, bidirectionality, consistency and completeness of the model
are discussed: all and only correct word forms are analysed or generated, even
alternative ones and gaps in paradigms are preserved. A Prolog implementation
has been developed for both analysis and generation of Spanish word forms. It
consists of only six DCG rules, because our {\em lexicalist\/} approach --i.e.
most information is in the dictionary. Although it is quite efficient, the
current implementation could be improved for analysis by using the non logical
features of Prolog, especially in word segmentation and dictionary access.
|
cmp-lg/9507005
|
Comparative Ellipsis and Variable Binding
|
cmp-lg cs.CL
|
In this paper, we discuss the question whether phrasal comparatives should be
given a direct interpretation, or require an analysis as elliptic
constructions, and answer it with Yes and No. The most adequate analysis of
wide reading attributive (WRA) comparatives seems to be as cases of ellipsis,
while a direct (but asymmetric) analysis fits the data for narrow scope
attributive comparatives. The question whether it is a syntactic or a semantic
process which provides the missing linguistic material in the complement of WRA
comparatives is also given a complex answer: Linguistic context is accessed by
combining a reconstruction operation and a mechanism of anaphoric reference.
The analysis makes only few and straightforward syntactic assumptions. In part,
this is made possible because the use of Generalized Functional Application as
a semantic operation allows us to model semantic composition in a flexible way.
|
cmp-lg/9507006
|
Transfer in a Connectionist Model of the Acquisition of Morphology
|
cmp-lg cs.CL
|
The morphological systems of natural languages are replete with examples of
the same devices used for multiple purposes: (1) the same type of morphological
process (for example, suffixation for both noun case and verb tense) and (2)
identical morphemes (for example, the same suffix for English noun plural and
possessive). These sorts of similarity would be expected to convey advantages
on language learners in the form of transfer from one morphological category to
another. Connectionist models of morphology acquisition have been faulted for
their supposed inability to represent phonological similarity across
morphological categories and hence to facilitate transfer. This paper describes
a connectionist model of the acquisition of morphology which is shown to
exhibit transfer of this type. The model treats the morphology acquisition
problem as one of learning to map forms onto meanings and vice versa. As the
network learns these mappings, it makes phonological generalizations which are
embedded in connection weights. Since these weights are shared by different
morphological categories, transfer is enabled. In a set of experiments with
artificial stimuli, networks were trained first on one morphological task
(e.g., tense) and then on a second (e.g., number). It is shown that in the
context of suffixation, prefixation, and template rules, the second task is
facilitated when the second category either makes use of the same forms or the
same general process type (e.g., prefixation) as the first.
|
cmp-lg/9507007
|
An Efficient Algorithm for Surface Generation
|
cmp-lg cs.CL
|
A method is given that "inverts" a logic grammar and displays it from the
point of view of the logical form, rather than from that of the word string.
LR-compiling techniques are used to allow a recursive-descent generation
algorithm to perform "functor merging" much in the same way as an LR parser
performs prefix merging.
This is an improvement on the semantic-head-driven generator that results in
a much smaller search space. The amount of semantic lookahead can be varied,
and appropriate tradeoff points between table size and resulting nondeterminism
can be found automatically.
|
cmp-lg/9507008
|
A Constraint-based Case Frame Lexicon Architecture
|
cmp-lg cs.CL
|
In Turkish, (and possibly in many other languages) verbs often convey several
meanings (some totally unrelated) when they are used with subjects, objects,
oblique objects, adverbial adjuncts, with certain lexical, morphological, and
semantic features, and co-occurrence restrictions. In addition to the usual
sense variations due to selectional restrictions on verbal arguments, in most
cases, the meaning conveyed by a case frame is idiomatic and not compositional,
with subtle constraints. In this paper, we present an approach to building a
constraint-based case frame lexicon for use in natural language processing in
Turkish, whose prototype we have implemented under the TFS system developed at
Univ. of Stuttgart.
A number of observations that we have made on Turkish have indicated that we
need something beyond the traditional transitive and intransitive distinction,
and utilize a framework where verb valence is considered as the obligatory
co-existence of an arbitrary subset of possible arguments along with the
obligatory exclusion of certain others, relative to a verb sense. Additional
morphological lexical and semantic constraints on the syntactic constituents
organized as a 5-tier constraint hierarchy, are utilized to map a given
syntactic structure case-fraame to a specific verb sense.
|
cmp-lg/9507009
|
Specifying Logic Programs in Controlled Natural Language
|
cmp-lg cs.CL
|
Writing specifications for computer programs is not easy since one has to
take into account the disparate conceptual worlds of the application domain and
of software development. To bridge this conceptual gap we propose controlled
natural language as a declarative and application-specific specification
language. Controlled natural language is a subset of natural language that can
be accurately and efficiently processed by a computer, but is expressive enough
to allow natural usage by non-specialists. Specifications in controlled natural
language are automatically translated into Prolog clauses, hence become formal
and executable. The translation uses a definite clause grammar (DCG) enhanced
by feature structures. Inter-text references of the specification, e.g.
anaphora, are resolved with the help of discourse representation theory (DRT).
The generated Prolog clauses are added to a knowledge base. We have implemented
a prototypical specification system that successfully processes the
specification of a simple automated teller machine.
|
cmp-lg/9507010
|
On-line Learning of Binary Lexical Relations Using Two-dimensional
Weighted Majority Algorithms
|
cmp-lg cs.CL
|
We consider the problem of learning a certain type of lexical semantic
knowledge that can be expressed as a binary relation between words, such as the
so-called sub-categorization of verbs (a verb-noun relation) and the compound
noun phrase relation (a noun-noun relation). Specifically, we view this problem
as an on-line learning problem in the sense of Littlestone's learning model in
which the learner's goal is to minimize the total number of prediction
mistakes. In the computational learning theory literature, Goldman, Rivest and
Schapire and subsequently Goldman and Warmuth have considered the on-line
learning problem for binary relations R : X * Y -> {0, 1} in which one of the
domain sets X can be partitioned into a relatively small number of types,
namely clusters consisting of behaviorally indistinguishable members of X. In
this paper, we extend this model and suppose that both of the sets X, Y can be
partitioned into a small number of types, and propose a host of prediction
algorithms which are two-dimensional extensions of Goldman and Warmuth's
weighted majority type algorithm proposed for the original model. We apply
these algorithms to the learning problem for the `compound noun phrase'
relation, in which a noun is related to another just in case they can form a
noun phrase together. Our experimental results show that all of our algorithms
out-perform Goldman and Warmuth's algorithm. We also theoretically analyze the
performance of one of our algorithms, in the form of an upper bound on the
worst case number of prediction mistakes it makes.
|
cmp-lg/9507011
|
Generalizing Case Frames Using a Thesaurus and the MDL Principle
|
cmp-lg cs.CL
|
We address the problem of automatically acquiring case-frame patterns from
large corpus data. In particular, we view this problem as the problem of
estimating a (conditional) distribution over a partition of words, and propose
a new generalization method based on the MDL (Minimum Description Length)
principle. In order to assist with the efficiency, our method makes use of an
existing thesaurus and restricts its attention on those partitions that are
present as `cuts' in the thesaurus tree, thus reducing the generalization
problem to that of estimating the `tree cut models' of the thesaurus. We then
give an efficient algorithm which provably obtains the optimal tree cut model
for the given frequency data, in the sense of MDL. We have used the case-frame
patterns obtained using our method to resolve pp-attachment ambiguity.Our
experimental results indicate that our method improves upon or is at least as
effective as existing methods.
|
cmp-lg/9507012
|
A Grammar Formalism and Cross-Serial Dependencies
|
cmp-lg cs.CL
|
First we define a unification grammar formalism called the Tree Homomorphic
Feature Structure Grammar. It is based on Lexical Functional Grammar (LFG), but
has a strong restriction on the syntax of the equations. We then show that this
grammar formalism defines a full abstract family of languages, and that it is
capable of describing cross-serial dependencies of the type found in Swiss
German.
|
cmp-lg/9507013
|
Indexed Languages and Unification Grammars
|
cmp-lg cs.CL
|
Indexed languages are interesting in computational linguistics because they
are the least class of languages in the Chomsky hierarchy that has not been
shown not to be adequate to describe the string set of natural language
sentences. We here define a class of unification grammars that exactly describe
the class of indexed languages.
|
cmp-lg/9507014
|
Co-Indexing Labelled DRSs to Represent and Reason with Ambiguities
|
cmp-lg cs.CL
|
The paper addresses the problem of representing ambiguities in a way that
allows for monotonic disambiguation and for direct deductive computation. The
paper focuses on an extension of the formalism of underspecified DRSs to
ambiguities introduced by plural NPs. It deals with the collective/distributive
distinction, and also with generic and cumulative readings. In addition it
provides a systematic account for an underspecified treatment of plural pronoun
resolution.
|
cmp-lg/9508001
|
Bridging as Coercive Accommodation
|
cmp-lg cs.CL
|
In this paper we discuss the notion of "bridging" in Discourse Representation
Theory as a tool to account for discourse referents that have only been
established implicitly, through the lexical semantics of other referents. In
doing so, we use ideas from Generative Lexicon theory, to introduce antecedents
for anaphoric expressions that cannot be "linked" to a proper antecedent, but
that do not need to be "accommodated" because they have some connection to the
network of discourse referents that is already established.
|
cmp-lg/9508002
|
A Compositional Treatment of Polysemous Arguments in Categorial Grammar
|
cmp-lg cs.CL
|
We discuss an extension of the standard logical rules (functional application
and abstraction) in Categorial Grammar (CG), in order to deal with some
specific cases of polysemy. We borrow from Generative Lexicon theory which
proposes the mechanism of {\em coercion}, next to a rich nominal lexical
semantic structure called {\em qualia structure}.
In a previous paper we introduced coercion into the framework of {\em
sign-based} Categorial Grammar and investigated its impact on traditional
Fregean compositionality. In this paper we will elaborate on this idea, mostly
working towards the introduction of a new semantic dimension. Where in current
versions of sign-based Categorial Grammar only two representations are derived:
a prosodic one (form) and a logical one (modelling), here we introduce also a
more detaled representation of the lexical semantics. This extra knowledge will
serve to account for linguistic phenomena like {\em metonymy\/}.
|
cmp-lg/9508003
|
A Robust Parsing Algorithm For Link Grammars
|
cmp-lg cs.CL
|
In this paper we present a robust parsing algorithm based on the link grammar
formalism for parsing natural languages. Our algorithm is a natural extension
of the original dynamic programming recognition algorithm which recursively
counts the number of linkages between two words in the input sentence. The
modified algorithm uses the notion of a null link in order to allow a
connection between any pair of adjacent words, regardless of their dictionary
definitions. The algorithm proceeds by making three dynamic programming passes.
In the first pass, the input is parsed using the original algorithm which
enforces the constraints on links to ensure grammaticality. In the second pass,
the total cost of each substring of words is computed, where cost is determined
by the number of null links necessary to parse the substring. The final pass
counts the total number of parses with minimal cost. All of the original
pruning techniques have natural counterparts in the robust algorithm. When used
together with memoization, these techniques enable the algorithm to run
efficiently with cubic worst-case complexity. We have implemented these ideas
and tested them by parsing the Switchboard corpus of conversational English.
This corpus is comprised of approximately three million words of text,
corresponding to more than 150 hours of transcribed speech collected from
telephone conversations restricted to 70 different topics. Although only a
small fraction of the sentences in this corpus are "grammatical" by standard
criteria, the robust link grammar parser is able to extract relevant structure
for a large portion of the sentences. We present the results of our experiments
using this system, including the analyses of selected and random sentences from
the corpus.
|
cmp-lg/9508004
|
Parsing English with a Link Grammar
|
cmp-lg cs.CL
|
We develop a formal grammatical system called a link grammar, show how
English grammar can be encoded in such a system, and give algorithms for
efficiently parsing with a link grammar. Although the expressive power of link
grammars is equivalent to that of context free grammars, encoding natural
language grammars appears to be much easier with the new system. We have
written a program for general link parsing and written a link grammar for the
English language. The performance of this preliminary system -- both in the
breadth of English phenomena that it captures and in the computational
resources used -- indicates that the approach may have practical uses as well
as linguistic significance. Our program is written in C and may be obtained
through the internet.
|
cmp-lg/9508005
|
A Matching Technique in Example-Based Machine Translation
|
cmp-lg cs.CL
|
This paper addresses an important problem in Example-Based Machine
Translation (EBMT), namely how to measure similarity between a sentence
fragment and a set of stored examples. A new method is proposed that measures
similarity according to both surface structure and content. A second
contribution is the use of clustering to make retrieval of the best matching
example from the database more efficient. Results on a large number of test
cases from the CELEX database are presented.
|
cmp-lg/9508006
|
Bi-Lexical Rules for Multi-Lexeme Translation in Lexicalist MT
|
cmp-lg cs.CL
|
The paper presents a prototype lexicalist Machine Translation system (based
on the so-called `Shake-and-Bake' approach of Whitelock (1992) consisting of an
analysis component, a dynamic bilingual lexicon, and a generation component,
and shows how it is applied to a range of MT problems. Multi-Lexeme
translations are handled through bi-lexical rules which map bilingual lexical
signs into new bilingual lexical signs. It is argued that much translation can
be handled by equating translationally equivalent lists of lexical signs,
either directly in the bilingual lexicon, or by deriving them through
bi-lexical rules. Lexical semantic information organized as Qualia structures
(Pustejovsky 1991) is used as a mechanism for restricting the domain of the
rules.
|
cmp-lg/9508007
|
A Dynamic Approach to Rhythm in Language: Toward a Temporal Phonology
|
cmp-lg cs.CL
|
It is proposed that the theory of dynamical systems offers appropriate tools
to model many phonological aspects of both speech production and perception. A
dynamic account of speech rhythm is shown to be useful for description of both
Japanese mora timing and English timing in a phrase repetition task. This
orientation contrasts fundamentally with the more familiar symbolic approach to
phonology, in which time is modeled only with sequentially arrayed symbols. It
is proposed that an adaptive oscillator offers a useful model for perceptual
entrainment (or `locking in') to the temporal patterns of speech production.
This helps to explain why speech is often perceived to be more regular than
experimental measurements seem to justify. Because dynamic models deal with
real time, they also help us understand how languages can differ in their
temporal detail---contributing to foreign accents, for example. The fact that
languages differ greatly in their temporal detail suggests that these effects
are not mere motor universals, but that dynamical models are intrinsic
components of the phonological characterization of language.
|
cmp-lg/9508008
|
On Constraint-Based Lambek Calculi
|
cmp-lg cs.CL
|
We explore the consequences of layering a Lambek proof system over an
arbitrary (constraint) logic. A simple model-theoretic semantics for our hybrid
language is provided for which a particularly simple combination of Lambek's
and the proof system of the base logic is complete. Furthermore the proof
system for the underlying base logic can be assumed to be a black box. The
essential reasoning needed to be performed by the black box is that of {\em
entailment checking}. Assuming feature logic as the base logic entailment
checking amounts to a {\em subsumption} test which is a well-known quasi-linear
time decidable problem.
|
cmp-lg/9508009
|
A Labelled Analytic Theorem Proving Environment for Categorial Grammar
|
cmp-lg cs.CL
|
We present a system for the investigation of computational properties of
categorial grammar parsing based on a labelled analytic tableaux theorem
prover. This proof method allows us to take a modular approach, in which the
basic grammar can be kept constant, while a range of categorial calculi can be
captured by assigning different properties to the labelling algebra. The
theorem proving strategy is particularly well suited to the treatment of
categorial grammar, because it allows us to distribute the computational cost
between the algorithm which deals with the grammatical types and the algebraic
checker which constrains the derivation.
|
cmp-lg/9508010
|
Heuristics and Parse Ranking
|
cmp-lg cs.CL
|
There are currently two philosophies for building grammars and parsers --
Statistically induced grammars and Wide-coverage grammars. One way to combine
the strengths of both approaches is to have a wide-coverage grammar with a
heuristic component which is domain independent but whose contribution is tuned
to particular domains. In this paper, we discuss a three-stage approach to
disambiguation in the context of a lexicalized grammar, using a variety of
domain independent heuristic techniques. We present a training algorithm which
uses hand-bracketed treebank parses to set the weights of these heuristics. We
compare the performance of our grammar against the performance of the IBM
statistical grammar, using both untrained and trained weights for the
heuristics.
|
cmp-lg/9508011
|
The Use of Knowledge Preconditions in Language Processing
|
cmp-lg cs.CL
|
If an agent does not possess the knowledge needed to perform an action, it
may privately plan to obtain the required information on its own, or it may
involve another agent in the planning process by engaging it in a dialogue. In
this paper, we show how the requirements of knowledge preconditions can be used
to account for information-seeking subdialogues in discourse. We first present
an axiomatization of knowledge preconditions for the SharedPlan model of
collaborative activity (Grosz & Kraus, 1993), and then provide an analysis of
information-seeking subdialogues within a general framework for discourse
processing. In this framework, SharedPlans and relationships among them are
used to model the intentional component of Grosz and Sidner's (1986) theory of
discourse structure.
|
cmp-lg/9508012
|
A Natural Law of Succession
|
cmp-lg cs.CL
|
Consider the problem of multinomial estimation. You are given an alphabet of
k distinct symbols and are told that the i-th symbol occurred exactly n_i times
in the past. On the basis of this information alone, you must now estimate the
conditional probability that the next symbol will be i. In this report, we
present a new solution to this fundamental problem in statistics and
demonstrate that our solution outperforms standard approaches, both in theory
and in practice.
|
cmp-lg/9509001
|
How much is enough?: Data requirements for statistical NLP
|
cmp-lg cs.CL
|
In this paper I explore a number of issues in the analysis of data
requirements for statistical NLP systems. A preliminary framework for viewing
such systems is proposed and a sample of existing works are compared within
this framework. The first steps toward a theory of data requirements are made
by establishing some results relevant to bounding the expected error rate of a
class of simplified statistical language learners as a function of the volume
of training data.
|
cmp-lg/9509002
|
Conserving Fuel in Statistical Language Learning: Predicting Data
Requirements
|
cmp-lg cs.CL
|
In this paper I address the practical concern of predicting how much training
data is sufficient for a statistical language learning system. First, I briefly
review earlier results and show how these can be combined to bound the expected
accuracy of a mode-based learner as a function of the volume of training data.
I then develop a more accurate estimate of the expected accuracy function under
the assumption that inputs are uniformly distributed. Since this estimate is
expensive to compute, I also give a close but cheaply computable approximation
to it. Finally, I report on a series of simulations exploring the effects of
inputs that are not uniformly distributed. Although these results are based on
simplistic assumptions, they are a tentative step toward a useful theory of
data requirements for SLL systems.
|
cmp-lg/9509003
|
Cluster Expansions and Iterative Scaling for Maximum Entropy Language
Models
|
cmp-lg cs.CL
|
The maximum entropy method has recently been successfully introduced to a
variety of natural language applications. In each of these applications,
however, the power of the maximum entropy method is achieved at the cost of a
considerable increase in computational requirements. In this paper we present a
technique, closely related to the classical cluster expansion from statistical
mechanics, for reducing the computational demands necessary to calculate
conditional maximum entropy language models.
|
cmp-lg/9509004
|
The Development and Migration of Concepts from Donor to Borrower
Disciplines: Sublanguage Term Use in Hard & Soft Sciences
|
cmp-lg cs.CL
|
Academic disciplines, often divided into hard and soft sciences, may be
understood as "donor disciplines" if they produce more concepts than they
borrow from other disciplines, or "borrower disciplines" if they import more
than they originate. Terms used to describe these concepts can be used to
distinguish between hard and soft, donor and borrower, as well as individual
discipline-specific sublanguages. Using term frequencies, the birth, growth,
death, and migration of concepts and their associated terms are examined.
|
cmp-lg/9509005
|
ParseTalk about Textual Ellipsis
|
cmp-lg cs.CL
|
A hybrid methodology for the resolution of text-level ellipsis is presented
in this paper. It incorporates conceptual proximity criteria applied to
ontologically well-engineered domain knowledge bases and an approach to
centering based on functional topic/comment patterns. We state text grammatical
predicates for ellipsis and then turn to the procedural aspects of their
evaluation within the framework of an actor-based implementation of a lexically
distributed parser.
|
cmp-lg/9510001
|
POS Tagging Using Relaxation Labelling
|
cmp-lg cs.CL
|
Relaxation labelling is an optimization technique used in many fields to
solve constraint satisfaction problems. The algorithm finds a combination of
values for a set of variables such that satisfies -to the maximum possible
degree- a set of given constraints. This paper describes some experiments
performed applying it to POS tagging, and the results obtained. It also ponders
the possibility of applying it to word sense disambiguation.
|
cmp-lg/9510002
|
Using Chinese Text Processing Technique for the Processing of Sanskrit
Based Indian Languages: Maximum Resource Utilization and Maximum
Compatibility
|
cmp-lg cs.CL
|
Chinese text processing systems are using Double Byte Coding , while almost
all existing Sanskrit Based Indian Languages have been using Single Byte coding
for text processing. Through observation, Chinese Information Processing
Technique has already achieved great technical development both in east and
west. In contrast,Indian Languages are being processed by computer, more or
less, for word processing purpose. This paper mainly emphasizes the method of
processing Indian languages from a Computational Linguistic point of view. An
overall design method is illustrated in this paper.This method concentrated on
maximum resource utilization and compatibility: the ultimate goal is to have a
Multiplatform Multilingual System. Keywords Text Procrssing, Multilingual Text
Processing, Chinese Language Processing, Indian Language Processing, Character
Coding.
|
cmp-lg/9510003
|
A Proposal for Word Sense Disambiguation using Conceptual Distance
|
cmp-lg cs.CL
|
This paper presents a method for the resolution of lexical ambiguity and its
automatic evaluation over the Brown Corpus. The method relies on the use of the
wide-coverage noun taxonomy of WordNet and the notion of conceptual distance
among concepts, captured by a Conceptual Density formula developed for this
purpose. This fully automatic method requires no hand coding of lexical
entries, hand tagging of text nor any kind of training process. The results of
the experiment have been automatically evaluated against SemCor, the
sense-tagged version of the Brown Corpus.
|
cmp-lg/9510004
|
Disambiguating bilingual nominal entries against WordNet
|
cmp-lg cs.CL
|
This paper explores the acquisition of conceptual knowledge from bilingual
dictionaries (French/English, Spanish/English and English/Spanish) using a
pre-existing broad coverage Lexical Knowledge Base (LKB) WordNet. Bilingual
nominal entries are disambiguated agains WordNet, therefore linking the
bilingual dictionaries to WordNet yielding a multilingual LKB (MLKB). The
resulting MLKB has the same structure as WordNet, but some nodes are attached
additionally to disambiguated vocabulary of other languages.
Two different, complementary approaches are explored. In one of the
approaches each entry of the dictionary is taken in turn, exploiting the
information in the entry itself. The inferential capability for disambiguating
the translation is given by Semantic Density over WordNet. In the other
approach, the bilingual dictionary was merged with WordNet, exploiting mainly
synonymy relations. Each of the approaches was used in a different dictionary.
Both approaches attain high levels of precision on their own, showing that
disambiguating bilingual nominal entries, and therefore linking bilingual
dictionaries to WordNet is a feasible task.
|
cmp-lg/9510005
|
Developing and Evaluating a Probabilistic LR Parser of Part-of-Speech
and Punctuation Labels
|
cmp-lg cs.CL
|
We describe an approach to robust domain-independent syntactic parsing of
unrestricted naturally-occurring (English) input. The technique involves
parsing sequences of part-of-speech and punctuation labels using a
unification-based grammar coupled with a probabilistic LR parser. We describe
the coverage of several corpora using this grammar and report the results of a
parsing experiment using probabilities derived from bracketed training data. We
report the first substantial experiments to assess the contribution of
punctuation to deriving an accurate syntactic analysis, by parsing identical
texts both with and without naturally-occurring punctuation marks.
|
cmp-lg/9510006
|
Incorporating Discourse Aspects in English -- Polish MT: Towards Robust
Implementation
|
cmp-lg cs.CL
|
The main aim of translation is an accurate transfer of meaning so that the
result is not only grammatically and lexically correct but also communicatively
adequate. This paper stresses the need for discourse analysis the aim of which
is to preserve the communicative meaning in English--Polish machine
translation. Unlike English, which is a positional language with word order
grammatically determined, Polish displays a strong tendency to order
constituents according to their degree of salience, so that the most
informationally salient elements are placed towards the end of the clause
regardless of their grammatical function. The Centering Theory developed for
tracking down given information units in English and the Theory of Functional
Sentence Perspective predicting informativeness of subsequent constituents
provide theoretical background for this work. The notion of {\em center} is
extended to accommodate not only for pronominalisation and exact reiteration
but also for definiteness and other center pointing constructs. Center
information is additionally graded and applicable to all primary constituents
in a given utterance. This information is used to order the post-transfer
constituents correctly, relying on statistical regularities and some syntactic
clues.
|
cmp-lg/9510007
|
Automatic Identification of Support Verbs: A Step Towards a Definition
of Semantic Weight
|
cmp-lg cs.CL
|
Current definitions of notions of lexical density and semantic weight are
based on the division of words into closed and open classes, and on intuition.
This paper develops a computationally tractable definition of semantic weight,
concentrating on what it means for a word to be semantically light; the
definition involves looking at the frequency of a word in particular syntactic
constructions which are indicative of lightness. Verbs such as "make" and
"take", when they function as support verbs, are often considered to be
semantically light. To test our definition, we carried out an experiment based
on that of Grefenstette and Teufel (1995), where we automatically identify
light instances of these words in a corpus; this was done by incorporating our
frequency-related definition of semantic weight into a statistical approach
similar to that of Grefenstette and Teufel. The results show that this is a
plausible definition of semantic lightness for verbs, which can possibly be
extended to defining semantic lightness for other classes of words.
|
cmp-lg/9510008
|
Toward an MT System without Pre-Editing --- Effects of New Methods in
ALT-J/E ---
|
cmp-lg cs.CL
|
Recently, several types of Japanese-to-English machine translation systems
have been developed, but all of them require an initial process of rewriting
the original text into easily translatable Japanese. Therefore these systems
are unsuitable for translating information that needs to be speedily
disseminated. To overcome this limitation, a Multi-Level Translation Method
based on the Constructive Process Theory has been proposed. This paper
describes the benefits of using this method in the Japanese-to-English machine
translation system ALT-J/E.
In comparison with conventional compositional methods, the Multi-Level
Translation Method emphasizes the importance of the meaning contained in
expression structures as a whole. It is shown to be capable of translating
typical written Japanese based on the meaning of the text in its context, with
comparative ease. We are now hopeful of carrying out useful machine translation
with no manual pre-editing.
|
cmp-lg/9511001
|
Countability and Number in Japanese-to-English Machine Translation
|
cmp-lg cs.CL
|
This paper presents a heuristic method that uses information in the Japanese
text along with knowledge of English countability and number stored in transfer
dictionaries to determine the countability and number of English noun phrases.
Incorporating this method into the machine translation system ALT-J/E, helped
to raise the percentage of noun phrases generated with correct use of articles
and number from 65% to 73%.
|
cmp-lg/9511002
|
Letting the Cat out of the Bag: Generation for Shake-and-Bake MT
|
cmp-lg cs.CL
|
Describes an algorithm for the generation phase of a Shake-and-Bake Machine
Translation system. Since the problem is NP-complete, it is unlikely that the
algorithm will be efficient in all cases, but for the cases tested it offers an
improvement over Whitelock's previously published algorithm. The work was
carried out while the author was employed at Sharp Laboratories of Europe Ltd.
|
cmp-lg/9511003
|
The Effect of Resource Limits and Task Complexity on Collaborative
Planning in Dialogue
|
cmp-lg cs.CL
|
This paper shows how agents' choice in communicative action can be designed
to mitigate the effect of their resource limits in the context of particular
features of a collaborative planning task. I first motivate a number of
hypotheses about effective language behavior based on a statistical analysis of
a corpus of natural collaborative planning dialogues. These hypotheses are then
tested in a dialogue testbed whose design is motivated by the corpus analysis.
Experiments in the testbed examine the interaction between (1) agents' resource
limits in attentional capacity and inferential capacity; (2) agents' choice in
communication; and (3) features of communicative tasks that affect task
difficulty such as inferential complexity, degree of belief coordination
required, and tolerance for errors. The results show that good algorithms for
communication must be defined relative to the agents' resource limits and the
features of the task. Algorithms that are inefficient for inferentially simple,
low coordination or fault-tolerant tasks are effective when tasks require
coordination or complex inferences, or are fault-intolerant. The results
provide an explanation for the occurrence of utterances in human dialogues
that, prima facie, appear inefficient, and provide the basis for the design of
effective algorithms for communicative choice for resource limited agents.
|
cmp-lg/9511004
|
An investigation into the correlation of cue phrases, unfilled pauses
and the structuring of spoken discourse
|
cmp-lg cs.CL
|
Expectations about the correlation of cue phrases, the duration of unfilled
pauses and the structuring of spoken discourse are framed in light of Grosz and
Sidner's theory of discourse and are tested for a directions-giving dialogue.
The results suggest that cue phrase and discourse structuring tasks may align,
and show a correlation for pause length and some of the modifications that
speakers can make to discourse structure.
|
cmp-lg/9511005
|
Chart-driven Connectionist Categorial Parsing of Spoken Korean
|
cmp-lg cs.CL
|
While most of the speech and natural language systems which were developed
for English and other Indo-European languages neglect the morphological
processing and integrate speech and natural language at the word level, for the
agglutinative languages such as Korean and Japanese, the morphological
processing plays a major role in the language processing since these languages
have very complex morphological phenomena and relatively simple syntactic
functionality. Obviously degenerated morphological processing limits the usable
vocabulary size for the system and word-level dictionary results in exponential
explosion in the number of dictionary entries. For the agglutinative languages,
we need sub-word level integration which leaves rooms for general morphological
processing. In this paper, we developed a phoneme-level integration model of
speech and linguistic processings through general morphological analysis for
agglutinative languages and a efficient parsing scheme for that integration.
Korean is modeled lexically based on the categorial grammar formalism with
unordered argument and suppressed category extensions, and chart-driven
connectionist parsing method is introduced.
|
cmp-lg/9511006
|
Disambiguating Noun Groupings with Respect to WordNet Senses
|
cmp-lg cs.CL
|
Word groupings useful for language processing tasks are increasingly
available, as thesauri appear on-line, and as distributional word clustering
techniques improve. However, for many tasks, one is interested in relationships
among word {\em senses}, not words. This paper presents a method for automatic
sense disambiguation of nouns appearing within sets of related nouns --- the
kind of data one finds in on-line thesauri, or as the output of distributional
clustering algorithms. Disambiguation is performed with respect to WordNet
senses, which are fairly fine-grained; however, the method also permits the
assignment of higher-level WordNet categories rather than sense labels. The
method is illustrated primarily by example, though results of a more rigorous
evaluation are also presented.
|
cmp-lg/9511007
|
Using Information Content to Evaluate Semantic Similarity in a Taxonomy
|
cmp-lg cs.CL
|
This paper presents a new measure of semantic similarity in an IS-A taxonomy,
based on the notion of information content. Experimental evaluation suggests
that the measure performs encouragingly well (a correlation of r = 0.79 with a
benchmark set of human similarity judgments, with an upper bound of r = 0.90
for human subjects performing the same task), and significantly better than the
traditional edge counting approach (r = 0.66).
|
cmp-lg/9512001
|
Analysis of the Arabic Broken Plural and Diminutive
|
cmp-lg cs.CL
|
This paper demonstrates how the challenging problem of the Arabic broken
plural and diminutive can be handled under a multi-tape two-level model, an
extension to two-level morphology.
|
cmp-lg/9512002
|
The Unsupervised Acquisition of a Lexicon from Continuous Speech
|
cmp-lg cs.CL
|
We present an unsupervised learning algorithm that acquires a
natural-language lexicon from raw speech. The algorithm is based on the optimal
encoding of symbol sequences in an MDL framework, and uses a hierarchical
representation of language that overcomes many of the problems that have
stymied previous grammar-induction procedures. The forward mapping from symbol
sequences to the speech stream is modeled using features based on articulatory
gestures. We present results on the acquisition of lexicons and language models
from raw speech, text, and phonetic transcripts, and demonstrate that our
algorithm compares very favorably to other reported results with respect to
segmentation performance and statistical efficiency.
|
cmp-lg/9512003
|
Limited Attention and Discourse Structure
|
cmp-lg cs.CL
|
This squib examines the role of limited attention in a theory of discourse
structure and proposes a model of attentional state that relates current
hierarchical theories of discourse structure to empirical evidence about human
discourse processing capabilities. First, I present examples that are not
predicted by Grosz and Sidner's stack model of attentional state. Then I
consider an alternative model of attentional state, the cache model, which
accounts for the examples, and which makes particular processing predictions.
Finally I suggest a number of ways that future research could distinguish the
predictions of the cache model and the stack model.
|
cmp-lg/9512004
|
Natural language processing: she needs something old and something new
(maybe something borrowed and something blue, too)
|
cmp-lg cs.CL
|
Given the present state of work in natural language processing, this address
argues first, that advance in both science and applications requires a revival
of concern about what language is about, broadly speaking the world; and
second, that an attack on the summarising task, which is made ever more
important by the growth of electronic text resources and requires an
understanding of the role of large-scale discourse structure in marking
important text content, is a good way forward.
|
cmp-lg/9512005
|
Term Encoding of Typed Feature Structures
|
cmp-lg cs.CL
|
This paper presents an approach to Prolog-style term encoding of typed
feature structures. The type feature structures to be encoded are constrained
by appropriateness conditions as in Carpenter's ALE system. But unlike ALE, we
impose a further independently motivated closed-world assumption. This
assumption allows us to apply term encoding in cases that were problematic for
previous approaches. In particular, previous approaches have ruled out multiple
inheritance and further specification of feature-value declarations on
subtypes. In the present approach, these spececial cases can be handled as
well, though with some increase in complexity. For grammars without multiple
inheritance and specification of feature values, the encoding presented here
reduces to that of previous approaches.
|
cmp-lg/9601001
|
Automatic Inference of DATR Theories
|
cmp-lg cs.CL
|
This paper presents an approach for the automatic acquisition of linguistic
knowledge from unstructured data. The acquired knowledge is represented in the
lexical knowledge representation language DATR. A set of transformation rules
that establish inheritance relationships and a default-inference algorithm make
up the basis components of the system. Since the overall approach is not
restricted to a special domain, the heuristic inference strategy uses criteria
to evaluate the quality of a DATR theory, where different domains may require
different criteria. The system is applied to the linguistic learning task of
German noun inflection.
|
cmp-lg/9601002
|
Generic rules and non-constituent coordination
|
cmp-lg cs.CL
|
We present a metagrammatical formalism, {\em generic rules}, to give a
default interpretation to grammar rules. Our formalism introduces a process of
{\em dynamic binding} interfacing the level of pure grammatical knowledge
representation and the parsing level. We present an approach to non-constituent
coordination within categorial grammars, and reformulate it as a generic rule.
This reformulation is context-free parsable and reduces drastically the search
space associated to the parsing task for such phenomena.
|
cmp-lg/9601003
|
Report of the Study Group on Assessment and Evaluation
|
cmp-lg cs.CL
|
This is an interim report discussing possible guidelines for the assessment
and evaluation of projects developing speech and language systems. It was
prepared at the request of the European Commission DG XIII by an ad hoc study
group, and is now being made available in the form in which it was submitted to
the Commission. However, the report is not an official European Commission
document, and does not reflect European Commission policy, official or
otherwise.
After a discussion of terminology, the report focusses on combining
user-centred and technology-centred assessment, and on how meaningful
comparisons can be made of a variety of systems performing different tasks for
different domains. The report outlines the kind of infra-structure that might
be required to support comparative assessment and evaluation of heterogenous
projects, and also the results of a questionnaire concerning different
approaches to evaluation.
|
cmp-lg/9601004
|
Similarity between Words Computed by Spreading Activation on an English
Dictionary
|
cmp-lg cs.CL
|
This paper proposes a method for measuring semantic similarity between words
as a new tool for text analysis. The similarity is measured on a semantic
network constructed systematically from a subset of the English dictionary,
LDOCE (Longman Dictionary of Contemporary English). Spreading activation on the
network can directly compute the similarity between any two words in the
Longman Defining Vocabulary, and indirectly the similarity of all the other
words in LDOCE. The similarity represents the strength of lexical cohesion or
semantic relation, and also provides valuable information about similarity and
coherence of texts.
|
cmp-lg/9601005
|
Text Segmentation Based on Similarity between Words
|
cmp-lg cs.CL
|
This paper proposes a new indicator of text structure, called the lexical
cohesion profile (LCP), which locates segment boundaries in a text. A text
segment is a coherent scene; the words in a segment are linked together via
lexical cohesion relations. LCP records mutual similarity of words in a
sequence of text. The similarity of words, which represents their cohesiveness,
is computed using a semantic network. Comparison with the text segments marked
by a number of subjects shows that LCP closely correlates with the human
judgments. LCP may provide valuable information for resolving anaphora and
ellipsis.
|
cmp-lg/9601006
|
Possessive Pronouns as Determiners in Japanese-to-English Machine
Translation
|
cmp-lg cs.CL
|
Possessive pronouns are used as determiners in English when no equivalent
would be used in a Japanese sentence with the same meaning. This paper proposes
a heuristic method of generating such possessive pronouns even when there is no
equivalent in the Japanese. The method uses information about the use of
possessive pronouns in English treated as a lexical property of nouns, in
addition to contextual information about noun phrase referentiality and the
subject and main verb of the sentence that the noun phrase appears in. The
proposed method has been implemented in NTT Communication Science Laboratories'
Japanese-to-English machine translation system ALT-J/E. In a test set of 6,200
sentences, the proposed method increased the number of noun phrases with
appropriate possessive pronouns generated, by 263 to 609, at the cost of
generating 83 noun phrases with inappropriate possessive pronouns.
|
cmp-lg/9601007
|
Context-Sensitive Measurement of Word Distance by Adaptive Scaling of a
Semantic Space
|
cmp-lg cs.CL
|
The paper proposes a computationally feasible method for measuring
context-sensitive semantic distance between words. The distance is computed by
adaptive scaling of a semantic space. In the semantic space, each word in the
vocabulary V is represented by a multi-dimensional vector which is obtained
from an English dictionary through a principal component analysis. Given a word
set C which specifies a context for measuring word distance, each dimension of
the semantic space is scaled up or down according to the distribution of C in
the semantic space. In the space thus transformed, distance between words in V
becomes dependent on the context C. An evaluation through a word prediction
task shows that the proposed measurement successfully extracts the context of a
text.
|
cmp-lg/9601008
|
Noun Phrase Reference in Japanese-to-English Machine Translation
|
cmp-lg cs.CL
|
This paper shows the necessity of distinguishing different referential uses
of noun phrases in machine translation. We argue that differentiating between
the generic, referential and ascriptive uses of noun phrases is the minimum
necessary to generate articles and number correctly when translating from
Japanese to English. Heuristics for determining these differences are proposed
for a Japanese-to-English machine translation system. Finally the results of
using the proposed heuristics are shown to have raised the percentage of noun
phrases generated with correct use of articles and number in the
Japanese-to-English machine translation system ALT-J/E from 65% to 77%.
|
cmp-lg/9601009
|
A General Architecture for Language Engineering (GATE) - a new approach
to Language Engineering R&D
|
cmp-lg cs.CL
|
This report argues for the provision of a common software infrastructure for
NLP systems. Current trends in Language Engineering research are reviewed as
motivation for this infrastructure, and relevant recent work discussed. A
freely-available system called GATE is described which builds on this work.
|
cmp-lg/9601010
|
Parsing with Typed Feature Structures
|
cmp-lg cs.CL
|
In this paper we provide for parsing with respect to grammars expressed in a
general TFS-based formalism, a restriction of ALE. Our motivation being the
design of an abstract (WAM-like) machine for the formalism, we consider parsing
as a computational process and use it as an operational semantics to guide the
design of the control structures for the abstract machine.
We emphasize the notion of abstract typed feature structures (AFSs) that
encode the essential information of TFSs and define unification over AFSs
rather than over TFSs. We then introduce an explicit construct of multi-rooted
feature structures (MRSs) that naturally extend TFSs and use them to represent
phrasal signs as well as grammar rules. We also employ abstractions of MRSs and
give the mathematical foundations needed for manipulating them. We then present
a simple bottom-up chart parser as a model for computation: grammars written in
the TFS-based formalism are executed by the parser. Finally, we show that the
parser is correct.
|
cmp-lg/9601011
|
Parsing with Typed Feature Structures
|
cmp-lg cs.CL
|
In this paper we provide for parsing with respect to grammars expressed in a
general TFS-based formalism, a restriction of ALE. Our motivation being the
design of an abstract (WAM-like) machine for the formalism, we consider parsing
as a computational process and use it as an operational semantics to guide the
design of the control structures for the abstract machine.
We emphasize the notion of abstract typed feature structures (AFSs) that
encode the essential information of TFSs and define unification over AFSs
rather than over TFSs. We then introduce an explicit construct of multi-rooted
feature structures (MRSs) that naturally extend TFSs and use them to represent
phrasal signs as well as grammar rules. We also employ abstractions of MRSs and
give the mathematical foundations needed for manipulating them. We formally
define grammars and the languages they generate, and then describe a model for
computation that corresponds to bottom-up chart parsing: grammars written in
the TFS-based formalism are executed by the parser. We show that the
computation is correct with respect to the independent definition. Finally, we
discuss the class of grammars for which computations terminate and prove that
termination can be guaranteed for off-line parsable grammars.
|
cmp-lg/9602001
|
How Part-of-Speech Tags Affect Text Retrieval and Filtering Performance
|
cmp-lg cs.CL
|
Natural language processing (NLP) applied to information retrieval (IR) and
filtering problems may assign part-of-speech tags to terms and, more generally,
modify queries and documents. Analytic models can predict the performance of a
text filtering system as it incorporates changes suggested by NLP, allowing us
to make precise statements about the average effect of NLP operations on IR.
Here we provide a model of retrieval and tagging that allows us to both compute
the performance change due to syntactic parsing and to allow us to understand
what factors affect performance and how. In addition to a prediction of
performance with tags, upper and lower bounds for retrieval performance are
derived, giving the best and worst effects of including part-of-speech tags.
Empirical grounds for selecting sets of tags are considered.
|
cmp-lg/9602002
|
Situations and Computation: An Overview of Recent Research
|
cmp-lg cs.CL
|
Serious thinking about the computational aspects of situation theory is just
starting. There have been some recent proposals in this direction (viz. PROSIT
and ASTL), with varying degrees of divergence from the ontology of the theory.
We believe that a programming environment incorporating bona fide
situation-theoretic constructs is needed and describe our very recent BABY-SIT
implementation. A detailed critical account of PROSIT and ASTL is also offered
in order to compare our system with these pioneering and influential
frameworks.
|
cmp-lg/9602003
|
Text Windows and Phrases Differing by Discipline, Location in Document,
and Syntactic Structure
|
cmp-lg cs.CL
|
Knowledge of window style, content, location and grammatical structure may be
used to classify documents as originating within a particular discipline or may
be used to place a document on a theory versus practice spectrum. This
distinction is also studied here using the type-token ratio to differentiate
between sublanguages. The statistical significance of windows is computed,
based on the the presence of terms in titles, abstracts, citations, and section
headers, as well as binary independent (BI) and inverse document frequency
(IDF) weightings. The characteristics of windows are studied by examining their
within window density (WWD) and the S concentration (SC), the concentration of
terms from various document fields (e.g. title, abstract) in the fulltext. The
rate of window occurrences from the beginning to the end of document fulltext
differs between academic fields. Different syntactic structures in sublanguages
are examined, and their use is considered for discriminating between specific
academic disciplines and, more generally, between theory versus practice or
knowledge versus applications oriented documents.
|
cmp-lg/9602004
|
Assessing agreement on classification tasks: the kappa statistic
|
cmp-lg cs.CL
|
Currently, computational linguists and cognitive scientists working in the
area of discourse and dialogue argue that their subjective judgments are
reliable using several different statistics, none of which are easily
interpretable or comparable to each other. Meanwhile, researchers in content
analysis have already experienced the same difficulties and come up with a
solution in the kappa statistic. We discuss what is wrong with reliability
measures as they are currently used for discourse and dialogue work in
computational linguistics and cognitive science, and argue that we would be
better off as a field adopting techniques from content analysis.
|
cmp-lg/9603001
|
Speech Recognition by Composition of Weighted Finite Automata
|
cmp-lg cs.CL
|
We present a general framework based on weighted finite automata and weighted
finite-state transducers for describing and implementing speech recognizers.
The framework allows us to represent uniformly the information sources and data
structures used in recognition, including context-dependent units,
pronunciation dictionaries, language models and lattices. Furthermore, general
but efficient algorithms can used for combining information sources in actual
recognizers and for optimizing their application. In particular, a single
composition algorithm is used both to combine in advance information sources
such as language models and dictionaries, and to combine acoustic observations
and information sources dynamically during recognition.
|
cmp-lg/9603002
|
Finite-State Approximation of Phrase-Structure Grammars
|
cmp-lg cs.CL
|
Phrase-structure grammars are effective models for important syntactic and
semantic aspects of natural languages, but can be computationally too demanding
for use as language models in real-time speech recognition. Therefore,
finite-state models are used instead, even though they lack expressive power.
To reconcile those two alternatives, we designed an algorithm to compute
finite-state approximations of context-free grammars and
context-free-equivalent augmented phrase-structure grammars. The approximation
is exact for certain context-free grammars generating regular languages,
including all left-linear and right-linear context-free grammars. The algorithm
has been used to build finite-state language models for limited-domain speech
recognition tasks.
|
cmp-lg/9603003
|
Attempto Controlled English (ACE)
|
cmp-lg cs.CL
|
Attempto Controlled English (ACE) allows domain specialists to interactively
formulate requirements specifications in domain concepts. ACE can be accurately
and efficiently processed by a computer, but is expressive enough to allow
natural usage. The Attempto system translates specification texts in ACE into
discourse representation structures and optionally into Prolog. Translated
specification texts are incrementally added to a knowledge base. This knowledge
base can be queried in ACE for verification, and it can be executed for
simulation, prototyping and validation of the specification.
|
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