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cmp-lg/9502039
|
Multilingual Sentence Categorization according to Language
|
cmp-lg cs.CL
|
In this paper, we describe an approach to sentence categorization which has
the originality to be based on natural properties of languages with no training
set dependency. The implementation is fast, small, robust and textual errors
tolerant. Tested for french, english, spanish and german discrimination, the
system gives very interesting results, achieving in one test 99.4% correct
assignments on real sentences.
The resolution power is based on grammatical words (not the most common
words) and alphabet. Having the grammatical words and the alphabet of each
language at its disposal, the system computes for each of them its likelihood
to be selected. The name of the language having the optimum likelihood will tag
the sentence --- but non resolved ambiguities will be maintained. We will
discuss the reasons which lead us to use these linguistic facts and present
several directions to improve the system's classification performance.
Categorization sentences with linguistic properties shows that difficult
problems have sometimes simple solutions.
|
cmp-lg/9503001
|
Using a Corpus for Teaching Turkish Morphology
|
cmp-lg cs.CL
|
This paper reports on the preliminary phase of our ongoing research towards
developing an intelligent tutoring environment for Turkish grammar. One of the
components of this environment is a corpus search tool which, among other
aspects of the language, will be used to present the learner sample sentences
along with their morphological analyses. Following a brief introduction to the
Turkish language and its morphology, the paper describes the morphological
analysis and ambiguity resolution used to construct the corpus used in the
search tool. Finally, implementation issues and details involving the user
interface of the tool are discussed.
|
cmp-lg/9503002
|
Computational dialectology in Irish Gaelic
|
cmp-lg cs.CL
|
Dialect groupings can be discovered objectively and automatically by cluster
analysis of phonetic transcriptions such as those found in a linguistic atlas.
The first step in the analysis, the computation of linguistic distance between
each pair of sites, can be computed as Levenshtein distance between phonetic
strings. This correlates closely with the much more laborious technique of
determining and counting isoglosses, and is more accurate than the more
familiar metric of computing Hamming distance based on whether vocabulary
entries match. In the actual clustering step, traditional agglomerative
clustering works better than the top-down technique of partitioning around
medoids. When agglomerative clustering of phonetic string comparison distances
is applied to Gaelic, reasonable dialect boundaries are obtained, corresponding
to national and (within Ireland) provincial boundaries.
|
cmp-lg/9503003
|
Tagging French -- comparing a statistical and a constraint-based method
|
cmp-lg cs.CL
|
In this paper we compare two competing approaches to part-of-speech tagging,
statistical and constraint-based disambiguation, using French as our test
language. We imposed a time limit on our experiment: the amount of time spent
on the design of our constraint system was about the same as the time we used
to train and test the easy-to-implement statistical model. We describe the two
systems and compare the results. The accuracy of the statistical method is
reasonably good, comparable to taggers for English. But the constraint-based
tagger seems to be superior even with the limited time we allowed ourselves for
rule development.
|
cmp-lg/9503004
|
Creating a tagset, lexicon and guesser for a French tagger
|
cmp-lg cs.CL
|
We earlier described two taggers for French, a statistical one and a
constraint-based one. The two taggers have the same tokeniser and morphological
analyser. In this paper, we describe aspects of this work concerned with the
definition of the tagset, the building of the lexicon, derived from an existing
two-level morphological analyser, and the definition of a lexical transducer
for guessing unknown words.
|
cmp-lg/9503005
|
A specification language for Lexical Functional Grammars
|
cmp-lg cs.CL
|
This paper defines a language L for specifying LFG grammars. This enables
constraints on LFG's composite ontology (c-structures synchronised with
f-structures) to be stated directly; no appeal to the LFG construction
algorithm is needed. We use L to specify schemata annotated rules and the LFG
uniqueness, completeness and coherence principles. Broader issues raised by
this work are noted and discussed.
|
cmp-lg/9503006
|
ParseTalk about Sentence- and Text-Level Anaphora
|
cmp-lg cs.CL
|
We provide a unified account of sentence-level and text-level anaphora within
the framework of a dependency-based grammar model. Criteria for anaphora
resolution within sentence boundaries rephrase major concepts from GB's binding
theory, while those for text-level anaphora incorporate an adapted version of a
Grosz-Sidner-style focus model.
|
cmp-lg/9503007
|
The Semantics of Motion
|
cmp-lg cs.CL
|
In this paper we present a semantic study of motion complexes (ie. of a
motion verb followed by a spatial preposition). We focus on the spatial and the
temporal intrinsic semantic properties of the motion verbs, on the one hand,
and of the spatial prepositions, on the other hand. Then, we address the
problem of combining these basic semantics in order to formally and
automatically derive the spatiotemporal semantics of a motion complex from the
spatiotemporal properties of its components.
|
cmp-lg/9503008
|
Ellipsis and Higher-Order Unification
|
cmp-lg cs.CL
|
We present a new method for characterizing the interpretive possibilities
generated by elliptical constructions in natural language. Unlike previous
analyses, which postulate ambiguity of interpretation or derivation in the full
clause source of the ellipsis, our analysis requires no such hidden ambiguity.
Further, the analysis follows relatively directly from an abstract statement of
the ellipsis interpretation problem. It predicts correctly a wide range of
interactions between ellipsis and other semantic phenomena such as quantifier
scope and bound anaphora. Finally, although the analysis itself is stated
nonprocedurally, it admits of a direct computational method for generating
interpretations.
|
cmp-lg/9503009
|
Distributional Part-of-Speech Tagging
|
cmp-lg cs.CL
|
This paper presents an algorithm for tagging words whose part-of-speech
properties are unknown. Unlike previous work, the algorithm categorizes word
tokens in context instead of word types. The algorithm is evaluated on the
Brown Corpus.
|
cmp-lg/9503010
|
Corpus-based Method for Automatic Identification of Support Verbs for
Nominalizations
|
cmp-lg cs.CL
|
Nominalization is a highly productive phenomena in most languages. The
process of nominalization ejects a verb from its syntactic role into a nominal
position. The original verb is often replaced by a semantically emptied support
verb (e.g., "make a proposal"). The choice of a support verb for a given
nominalization is unpredictable, causing a problem for language learners as
well as for natural language processing systems. We present here a method of
discovering support verbs from an untagged corpus via low-level syntactic
processing and comparison of arguments attached to verbal forms and potential
nominalized forms. The result of the process is a list of potential support
verbs for the nominalized form of a given predicate.
|
cmp-lg/9503011
|
Improving Statistical Language Model Performance with Automatically
Generated Word Hierarchies
|
cmp-lg cs.CL
|
An automatic word classification system has been designed which processes
word unigram and bigram frequency statistics extracted from a corpus of natural
language utterances. The system implements a binary top-down form of word
clustering which employs an average class mutual information metric. Resulting
classifications are hierarchical, allowing variable class granularity. Words
are represented as structural tags --- unique $n$-bit numbers the most
significant bit-patterns of which incorporate class information. Access to a
structural tag immediately provides access to all classification levels for the
corresponding word. The classification system has successfully revealed some of
the structure of English, from the phonemic to the semantic level. The system
has been compared --- directly and indirectly --- with other recent word
classification systems. Class based interpolated language models have been
constructed to exploit the extra information supplied by the classifications
and some experiments have shown that the new models improve model performance.
|
cmp-lg/9503012
|
A Note on Zipf's Law, Natural Languages, and Noncoding DNA regions
|
cmp-lg cs.CL q-bio
|
In Phys. Rev. Letters (73:2, 5 Dec. 94), Mantegna et al. conclude on the
basis of Zipf rank frequency data that noncoding DNA sequence regions are more
like natural languages than coding regions. We argue on the contrary that an
empirical fit to Zipf's ``law'' cannot be used as a criterion for similarity to
natural languages. Although DNA is a presumably an ``organized system of
signs'' in Mandelbrot's (1961) sense, an observation of statistical features of
the sort presented in the Mantegna et al. paper does not shed light on the
similarity between DNA's ``grammar'' and natural language grammars, just as the
observation of exact Zipf-like behavior cannot distinguish between the
underlying processes of tossing an $M$ sided die or a finite-state branching
process.
|
cmp-lg/9503013
|
Incremental Interpretation: Applications, Theory, and Relationship to
Dynamic Semantics
|
cmp-lg cs.CL
|
Why should computers interpret language incrementally? In recent years
psycholinguistic evidence for incremental interpretation has become more and
more compelling, suggesting that humans perform semantic interpretation before
constituent boundaries, possibly word by word. However, possible computational
applications have received less attention. In this paper we consider various
potential applications, in particular graphical interaction and dialogue. We
then review the theoretical and computational tools available for mapping from
fragments of sentences to fully scoped semantic representations. Finally, we
tease apart the relationship between dynamic semantics and incremental
interpretation.
|
cmp-lg/9503014
|
Non-Constituent Coordination: Theory and Practice
|
cmp-lg cs.CL
|
Despite the large amount of theoretical work done on non-constituent
coordination during the last two decades, many computational systems still
treat coordination using adapted parsing strategies, in a similar fashion to
the SYSCONJ system developed for ATNs. This paper reviews the theoretical
literature, and shows why many of the theoretical accounts actually have worse
coverage than accounts based on processing. Finally, it shows how processing
accounts can be described formally and declaratively in terms of Dynamic
Grammars.
|
cmp-lg/9503015
|
Incremental Interpretation of Categorial Grammar
|
cmp-lg cs.CL
|
The paper describes a parser for Categorial Grammar which provides fully word
by word incremental interpretation. The parser does not require fragments of
sentences to form constituents, and thereby avoids problems of spurious
ambiguity. The paper includes a brief discussion of the relationship between
basic Categorial Grammar and other formalisms such as HPSG, Dependency Grammar
and the Lambek Calculus. It also includes a discussion of some of the issues
which arise when parsing lexicalised grammars, and the possibilities for using
statistical techniques for tuning to particular languages.
|
cmp-lg/9503016
|
Natural Language Interfaces to Databases - An Introduction
|
cmp-lg cs.CL
|
This paper is an introduction to natural language interfaces to databases
(NLIDBs). A brief overview of the history of NLIDBs is first given. Some
advantages and disadvantages of NLIDBs are then discussed, comparing NLIDBs to
formal query languages, form-based interfaces, and graphical interfaces. An
introduction to some of the linguistic problems NLIDBs have to confront
follows, for the benefit of readers less familiar with computational
linguistics. The discussion then moves on to NLIDB architectures, portability
issues, restricted natural language input systems (including menu-based
NLIDBs), and NLIDBs with reasoning capabilities. Some less explored areas of
NLIDB research are then presented, namely database updates, meta-knowledge
questions, temporal questions, and multi-modal NLIDBs. The paper ends with
reflections on the current state of the art.
|
cmp-lg/9503017
|
Redundancy in Collaborative Dialogue
|
cmp-lg cs.CL
|
In dialogues in which both agents are autonomous, each agent deliberates
whether to accept or reject the contributions of the current speaker. A speaker
cannot simply assume that a proposal or an assertion will be accepted. However,
an examination of a corpus of naturally-occurring problem-solving dialogues
shows that agents often do not explicitly indicate acceptance or rejection.
Rather the speaker must infer whether the hearer understands and accepts the
current contribution based on indirect evidence provided by the hearer's next
dialogue contribution. In this paper, I propose a model of the role of
informationally redundant utterances in providing evidence to support
inferences about mutual understanding and acceptance. The model (1) requires a
theory of mutual belief that supports mutual beliefs of various strengths; (2)
explains the function of a class of informationally redundant utterances that
cannot be explained by other accounts; and (3) contributes to a theory of
dialogue by showing how mutual beliefs can be inferred in the absence of the
master-slave assumption.
|
cmp-lg/9503018
|
Discourse and Deliberation: Testing a Collaborative Strategy
|
cmp-lg cs.CL
|
A discourse strategy is a strategy for communicating with another agent.
Designing effective dialogue systems requires designing agents that can choose
among discourse strategies. We claim that the design of effective strategies
must take cognitive factors into account, propose a new method for testing the
hypothesized factors, and present experimental results on an effective strategy
for supporting deliberation. The proposed method of computational dialogue
simulation provides a new empirical basis for computational linguistics.
|
cmp-lg/9503019
|
SATZ - An Adaptive Sentence Segmentation System
|
cmp-lg cs.CL
|
This paper provides a detailed description of the sentence segmentation
system first introduced in cmp-lg/9411022. It provides results of systematic
experiments involving sentence boundary determination, including context size,
lexicon size, and single-case texts. Also included are the results of
successfully adapting the system to German and French. The source code for the
system is available as a compressed tar file at
ftp://cs-tr.CS.Berkeley.EDU/pub/cstr/satz.tar.Z .
|
cmp-lg/9503020
|
Different Issues in the Design of a Lemmatizer/Tagger for Basque
|
cmp-lg cs.CL
|
This paper presents relevant issues that have been considered in the design
of a general purpose lemmatizer/tagger for Basque (EUSLEM). The
lemmatizer/tagger is conceived as a basic tool necessary for other linguistic
applications. It uses the lexical data base and the morphological analyzer
previously developed and implemented. Due to the characteristics of the
language, the tagset here proposed in structured in for levels, so that each
level is a refinement of the previous one in the sense that it adds more
detailed information. We will focus on the problems found in designing this
tagset and on the strategies for morphological disambiguation that will be
used.
|
cmp-lg/9503021
|
A Note on the Complexity of Restricted Attribute-Value Grammars
|
cmp-lg cs.CL
|
The recognition problem for attribute-value grammars (AVGs) was shown to be
undecidable by Johnson in 1988. Therefore, the general form of AVGs is of no
practical use. In this paper we study a very restricted form of AVG, for which
the recognition problem is decidable (though still NP-complete), the R-AVG. We
show that the R-AVG formalism captures all of the context free languages and
more, and introduce a variation on the so-called `off-line parsability
constraint', the `honest parsability constraint', which lets different types of
R-AVG coincide precisely with well-known time complexity classes.
|
cmp-lg/9503022
|
Assessing Complexity Results in Feature Theories
|
cmp-lg cs.CL
|
In this paper, we assess the complexity results of formalisms that describe
the feature theories used in computational linguistics. We show that from these
complexity results no immediate conclusions can be drawn about the complexity
of the recognition problem of unification grammars using these feature
theories. On the one hand, the complexity of feature theories does not provide
an upper bound for the complexity of such unification grammars.
On the other hand, the complexity of feature theories need not provide a
lower bound. Therefore, we argue for formalisms that describe actual
unification grammars instead of feature theories. Thus the complexity results
of these formalisms judge upon the hardness of unification grammars in
computational linguistics.
|
cmp-lg/9503023
|
A fast partial parse of natural language sentences using a connectionist
method
|
cmp-lg cs.CL
|
The pattern matching capabilities of neural networks can be used to locate
syntactic constituents of natural language. This paper describes a fully
automated hybrid system, using neural nets operating within a grammatic
framework. It addresses the representation of language for connectionist
processing, and describes methods of constraining the problem size. The
function of the network is briefly explained, and results are given.
|
cmp-lg/9503024
|
From compositional to systematic semantics
|
cmp-lg cs.CL
|
We prove a theorem stating that any semantics can be encoded as a
compositional semantics, which means that, essentially, the standard definition
of compositionality is formally vacuous. We then show that when compositional
semantics is required to be "systematic" (that is, the meaning function cannot
be arbitrary, but must belong to some class), it is possible to distinguish
between compositional and non-compositional semantics. As a result, we believe
that the paper clarifies the concept of compositionality and opens a
possibility of making systematic formal comparisons of different systems of
grammars.
|
cmp-lg/9503025
|
Co-occurrence Vectors from Corpora vs. Distance Vectors from
Dictionaries
|
cmp-lg cs.CL
|
A comparison was made of vectors derived by using ordinary co-occurrence
statistics from large text corpora and of vectors derived by measuring the
inter-word distances in dictionary definitions. The precision of word sense
disambiguation by using co-occurrence vectors from the 1987 Wall Street Journal
(20M total words) was higher than that by using distance vectors from the
Collins English Dictionary (60K head words + 1.6M definition words). However,
other experimental results suggest that distance vectors contain some different
semantic information from co-occurrence vectors.
|
cmp-lg/9504001
|
Automatic processing proper names in texts
|
cmp-lg cs.CL
|
This paper shows first the problems raised by proper names in natural
language processing. Second, it introduces the knowledge representation
structure we use based on conceptual graphs. Then it explains the techniques
which are used to process known and unknown proper names. At last, it gives the
performance of the system and the further works we intend to deal with.
|
cmp-lg/9504002
|
Tagset Design and Inflected Languages
|
cmp-lg cs.CL
|
An experiment designed to explore the relationship between tagging accuracy
and the nature of the tagset is described, using corpora in English, French and
Swedish. In particular, the question of internal versus external criteria for
tagset design is considered, with the general conclusion that external
(linguistic) criteria should be followed. Some problems associated with tagging
unknown words in inflected languages are briefly considered.
|
cmp-lg/9504003
|
Collaborating on Referring Expressions
|
cmp-lg cs.CL
|
This paper presents a computational model of how conversational participants
collaborate in order to make a referring action successful. The model is based
on the view of language as goal-directed behavior. We propose that the content
of a referring expression can be accounted for by the planning paradigm. Not
only does this approach allow the processes of building referring expressions
and identifying their referents to be captured by plan construction and plan
inference, it also allows us to account for how participants clarify a
referring expression by using meta-actions that reason about and manipulate the
plan derivation that corresponds to the referring expression. To account for
how clarification goals arise and how inferred clarification plans affect the
agent, we propose that the agents are in a certain state of mind, and that this
state includes an intention to achieve the goal of referring and a plan that
the agents are currently considering. It is this mental state that sanctions
the adoption of goals and the acceptance of inferred plans, and so acts as a
link between understanding and generation.
|
cmp-lg/9504004
|
A Computational Treatment of HPSG Lexical Rules as Covariation in
Lexical Entries
|
cmp-lg cs.CL
|
We describe a compiler which translates a set of HPSG lexical rules and their
interaction into definite relations used to constrain lexical entries. The
compiler ensures automatic transfer of properties unchanged by a lexical rule.
Thus an operational semantics for the full lexical rule mechanism as used in
HPSG linguistics is provided. Program transformation techniques are used to
advance the resulting encoding. The final output constitutes a computational
counterpart of the linguistic generalizations captured by lexical rules and
allows ``on the fly'' application.
|
cmp-lg/9504005
|
Constraint Logic Programming for Natural Language Processing
|
cmp-lg cs.CL
|
This paper proposes an evaluation of the adequacy of the constraint logic
programming paradigm for natural language processing. Theoretical aspects of
this question have been discussed in several works. We adopt here a pragmatic
point of view and our argumentation relies on concrete solutions. Using actual
contraints (in the CLP sense) is neither easy nor direct. However, CLP can
improve parsing techniques in several aspects such as concision, control,
efficiency or direct representation of linguistic formalism. This discussion is
illustrated by several examples and the presentation of an HPSG parser.
|
cmp-lg/9504006
|
Cues and control in Expert-Client Dialogues
|
cmp-lg cs.CL
|
We conducted an empirical analysis into the relation between control and
discourse structure. We applied control criteria to four dialogues and
identified 3 levels of discourse structure. We investigated the mechanism for
changing control between these structures and found that utterance type and not
cue words predicted shifts of control. Participants used certain types of
signals when discourse goals were proceeding successfully but resorted to
interruptions when they were not.
|
cmp-lg/9504007
|
Mixed Initiative in Dialogue: An Investigation into Discourse
Segmentation
|
cmp-lg cs.CL
|
Conversation between two people is usually of mixed-initiative, with control
over the conversation being transferred from one person to another. We apply a
set of rules for the transfer of control to 4 sets of dialogues consisting of a
total of 1862 turns. The application of the control rules lets us derive
domain-independent discourse structures. The derived structures indicate that
initiative plays a role in the structuring of discourse. In order to explore
the relationship of control and initiative to discourse processes like
centering, we analyze the distribution of four different classes of anaphora
for two data sets. This distribution indicates that some control segments are
hierarchically related to others. The analysis suggests that discourse
participants often mutually agree to a change of topic. We also compared
initiative in Task Oriented and Advice Giving dialogues and found that both
allocation of control and the manner in which control is transferred is
radically different for the two dialogue types. These differences can be
explained in terms of collaborative planning principles.
|
cmp-lg/9504008
|
SKOPE: A connectionist/symbolic architecture of spoken Korean processing
|
cmp-lg cs.CL
|
Spoken language processing requires speech and natural language integration.
Moreover, spoken Korean calls for unique processing methodology due to its
linguistic characteristics. This paper presents SKOPE, a connectionist/symbolic
spoken Korean processing engine, which emphasizes that: 1) connectionist and
symbolic techniques must be selectively applied according to their relative
strength and weakness, and 2) the linguistic characteristics of Korean must be
fully considered for phoneme recognition, speech and language integration, and
morphological/syntactic processing. The design and implementation of SKOPE
demonstrates how connectionist/symbolic hybrid architectures can be constructed
for spoken agglutinative language processing. Also SKOPE presents many novel
ideas for speech and language processing. The phoneme recognition,
morphological analysis, and syntactic analysis experiments show that SKOPE is a
viable approach for the spoken Korean processing.
|
cmp-lg/9504009
|
Abstract Machine for Typed Feature Structures
|
cmp-lg cs.CL
|
This paper describes an abstract machine for linguistic formalisms that are
based on typed feature structures, such as HPSG. The core design of the
abstract machine is given in detail, including the compilation process from a
high-level language to the abstract machine language and the implementation of
the abstract instructions. The machine's engine supports the unification of
typed, possibly cyclic, feature structures. A separate module deals with
control structures and instructions to accommodate parsing for phrase structure
grammars. We treat the linguistic formalism as a high-level declarative
programming language, applying methods that were proved useful in computer
science to the study of natural languages: a grammar specified using the
formalism is endowed with an operational semantics.
|
cmp-lg/9504010
|
MAXIMUM LIKELIHOOD AND MINIMUM ENTROPY IDENTIFICATION OF GRAMMARS
|
cmp-lg cs.CL
|
Using the Thermodynamic Formalism, we introduce a Gibbsian model for the
identification of regular grammars based only on positive evidence. This model
mimics the natural language acquisition procedure driven by prosody which is
here represented by the thermodynamical potential. The statistical question we
face is how to estimate the incidenc e matrix of a subshift of finite type from
a sample produced by a Gibbs state whose potential is known. The model
acquaints for both the robustness of t he language acquisition procedure and
language changes. The probabilistic appr oach we use avoids invoking ad-hoc
restrictions as Berwick's Subset Principle.
|
cmp-lg/9504011
|
A Processing Model for Free Word Order Languages
|
cmp-lg cs.CL
|
Like many verb-final languages, Germn displays considerable word-order
freedom: there is no syntactic constraint on the ordering of the nominal
arguments of a verb, as long as the verb remains in final position. This effect
is referred to as ``scrambling'', and is interpreted in transformational
frameworks as leftward movement of the arguments. Furthermore, arguments from
an embedded clause may move out of their clause; this effect is referred to as
``long-distance scrambling''. While scrambling has recently received
considerable attention in the syntactic literature, the status of long-distance
scrambling has only rarely been addressed. The reason for this is the
problematic status of the data: not only is long-distance scrambling highly
dependent on pragmatic context, it also is strongly subject to degradation due
to processing constraints. As in the case of center-embedding, it is not
immediately clear whether to assume that observed unacceptability of highly
complex sentences is due to grammatical restrictions, or whether we should
assume that the competence grammar does not place any restrictions on
scrambling (and that, therefore, all such sentences are in fact grammatical),
and the unacceptability of some (or most) of the grammatically possible word
orders is due to processing limitations. In this paper, we will argue for the
second view by presenting a processing model for German.
|
cmp-lg/9504012
|
Linear Logic for Meaning Assembly
|
cmp-lg cs.CL
|
Semantic theories of natural language associate meanings with utterances by
providing meanings for lexical items and rules for determining the meaning of
larger units given the meanings of their parts. Meanings are often assumed to
combine via function application, which works well when constituent structure
trees are used to guide semantic composition. However, we believe that the
functional structure of Lexical-Functional Grammar is best used to provide the
syntactic information necessary for constraining derivations of meaning in a
cross-linguistically uniform format. It has been difficult, however, to
reconcile this approach with the combination of meanings by function
application. In contrast to compositional approaches, we present a deductive
approach to assembling meanings, based on reasoning with constraints, which
meshes well with the unordered nature of information in the functional
structure. Our use of linear logic as a `glue' for assembling meanings allows
for a coherent treatment of the LFG requirements of completeness and coherence
as well as of modification and quantification.
|
cmp-lg/9504013
|
NLG vs. Templates
|
cmp-lg cs.CL
|
One of the most important questions in applied NLG is what benefits (or
`value-added', in business-speak) NLG technology offers over template-based
approaches. Despite the importance of this question to the applied NLG
community, however, it has not been discussed much in the research NLG
community, which I think is a pity. In this paper, I try to summarize the
issues involved and recap current thinking on this topic. My goal is not to
answer this question (I don't think we know enough to be able to do so), but
rather to increase the visibility of this issue in the research community, in
the hope of getting some input and ideas on this very important question. I
conclude with a list of specific research areas I would like to see more work
in, because I think they would increase the `value-added' of NLG over
templates.
|
cmp-lg/9504014
|
LexGram - a practical categorial grammar formalism -
|
cmp-lg cs.CL
|
We present the LexGram system, an amalgam of (Lambek) categorial grammar and
Head Driven Phrase Structure Grammar (HPSG), and show that the grammar
formalism it implements is a well-structured and useful tool for actual grammar
development.
|
cmp-lg/9504015
|
Estimating Lexical Priors for Low-Frequency Syncretic Forms
|
cmp-lg cs.CL
|
Given a previously unseen form that is morphologically n-ways ambiguous, what
is the best estimator for the lexical prior probabilities for the various
functions of the form? We argue that the best estimator is provided by
computing the relative frequencies of the various functions among the hapax
legomena --- the forms that occur exactly once in a corpus. This result has
important implications for the development of stochastic morphological taggers,
especially when some initial hand-tagging of a corpus is required: For
predicting lexical priors for very low-frequency morphologically ambiguous
types (most of which would not occur in any given corpus) one should
concentrate on tagging a good representative sample of the hapax legomena,
rather than extensively tagging words of all frequency ranges.
|
cmp-lg/9504016
|
Memoization of Top Down Parsing
|
cmp-lg cs.CL
|
This paper discusses the relationship between memoized top-down recognizers
and chart parsers. It presents a version of memoization suitable for
continuation-passing style programs. When applied to a simple formalization of
a top-down recognizer it yields a terminating parser.
|
cmp-lg/9504017
|
A Uniform Treatment of Pragmatic Inferences in Simple and Complex
Utterances and Sequences of Utterances
|
cmp-lg cs.CL
|
Drawing appropriate defeasible inferences has been proven to be one of the
most pervasive puzzles of natural language processing and a recurrent problem
in pragmatics. This paper provides a theoretical framework, called ``stratified
logic'', that can accommodate defeasible pragmatic inferences. The framework
yields an algorithm that computes the conversational, conventional, scalar,
clausal, and normal state implicatures; and the presuppositions that are
associated with utterances. The algorithm applies equally to simple and complex
utterances and sequences of utterances.
|
cmp-lg/9504018
|
An Implemented Formalism for Computing Linguistic Presuppositions and
Existential Commitments
|
cmp-lg cs.CL
|
We rely on the strength of linguistic and philosophical perspectives in
constructing a framework that offers a unified explanation for presuppositions
and existential commitment. We use a rich ontology and a set of methodological
principles that embed the essence of Meinong's philosophy and Grice's
conversational principles into a stratified logic, under an unrestricted
interpretation of the quantifiers. The result is a logical formalism that
yields a tractable computational method that uniformly calculates all the
presuppositions of a given utterance, including the existential ones.
|
cmp-lg/9504019
|
A Formalism and an Algorithm for Computing Pragmatic Inferences and
Detecting Infelicities
|
cmp-lg cs.CL
|
Since Austin introduced the term ``infelicity'', the linguistic literature
has been flooded with its use, but no formal or computational explanation has
been given for it. This thesis provides one for those infelicities that occur
when a pragmatic inference is cancelled.
Our contribution assumes the existence of a finer grained taxonomy with
respect to pragmatic inferences. It is shown that if one wants to account for
the natural language expressiveness, one should distinguish between pragmatic
inferences that are felicitous to defeat and pragmatic inferences that are
infelicitously defeasible. Thus, it is shown that one should consider at least
three types of information: indefeasible, felicitously defeasible, and
infelicitously defeasible. The cancellation of the last of these determines the
pragmatic infelicities.
A new formalism has been devised to accommodate the three levels of
information, called ``stratified logic''. Within it, we are able to express
formally notions such as ``utterance U presupposes P'' or ``utterance U is
infelicitous''. Special attention is paid to the implications that our work has
in solving some well-known existential philosophical puzzles. The formalism
yields an algorithm for computing interpretations for utterances, for
determining their associated presuppositions, and for signalling infelicitous
utterances that has been implemented in Common Lisp. The algorithm applies
equally to simple and complex utterances and sequences of utterances.
|
cmp-lg/9504020
|
Computational Interpretations of the Gricean Maxims in the Generation of
Referring Expressions
|
cmp-lg cs.CL
|
We examine the problem of generating definite noun phrases that are
appropriate referring expressions; i.e, noun phrases that (1) successfully
identify the intended referent to the hearer whilst (2) not conveying to her
any false conversational implicatures (Grice, 1975). We review several possible
computational interpretations of the conversational implicature maxims, with
different computational costs, and argue that the simplest may be the best,
because it seems to be closest to what human speakers do. We describe our
recommended algorithm in detail, along with a specification of the resources a
host system must provide in order to make use of the algorithm, and an
implementation used in the natural language generation component of the IDAS
system.
This paper will appear in the the April--June 1995 issue of Cognitive
Science, and is made available on cmp-lg with the permission of Ablex, the
publishers of that journal.
|
cmp-lg/9504021
|
Phonological Derivation in Optimality Theory
|
cmp-lg cs.CL
|
Optimality Theory is a constraint-based theory of phonology which allows
constraints to be violated. Consequently, implementing the theory presents
problems for declarative constraint-based processing frameworks. On the basis
of two regularity assumptions, that candidate sets are regular and that
constraints can be modelled by transducers, this paper presents and proves
correct algorithms for computing the action of constraints, and hence deriving
surface forms.
|
cmp-lg/9504022
|
Constraints, Exceptions and Representations
|
cmp-lg cs.CL
|
This paper shows that default-based phonologies have the potential to capture
morphophonological generalisations which cannot be captured by non-defaul
theories. In achieving this result, I offer a characterisation of
Underspecification Theory and Optimality Theory in terms of their methods for
ordering defaults. The result means that machine learning techniques for
building non-defualt analyses may not provide a suitable basis for
morphophonological analysis.
|
cmp-lg/9504023
|
TAKTAG: Two-phase learning method for hybrid statistical/rule-based
part-of-speech disambiguation
|
cmp-lg cs.CL
|
Both statistical and rule-based approaches to part-of-speech (POS)
disambiguation have their own advantages and limitations. Especially for
Korean, the narrow windows provided by hidden markov model (HMM) cannot cover
the necessary lexical and long-distance dependencies for POS disambiguation. On
the other hand, the rule-based approaches are not accurate and flexible to new
tag-sets and languages. In this regard, the statistical/rule-based hybrid
method that can take advantages of both approaches is called for the robust and
flexible POS disambiguation. We present one of such method, that is, a
two-phase learning architecture for the hybrid statistical/rule-based POS
disambiguation, especially for Korean. In this method, the statistical learning
of morphological tagging is error-corrected by the rule-based learning of Brill
[1992] style tagger. We also design the hierarchical and flexible Korean
tag-set to cope with the multiple tagging applications, each of which requires
different tag-set. Our experiments show that the two-phase learning method can
overcome the undesirable features of solely HMM-based or solely rule-based
tagging, especially for morphologically complex Korean.
|
cmp-lg/9504024
|
A Morphographemic Model for Error Correction in Nonconcatenative Strings
|
cmp-lg cs.CL
|
This paper introduces a spelling correction system which integrates
seamlessly with morphological analysis using a multi-tape formalism. Handling
of various Semitic error problems is illustrated, with reference to Arabic and
Syriac examples. The model handles errors vocalisation, diacritics, phonetic
syncopation and morphographemic idiosyncrasies, in addition to Damerau errors.
A complementary correction strategy for morphologically sound but
morphosyntactically ill-formed words is outlined.
|
cmp-lg/9504025
|
Discourse Processing of Dialogues with Multiple Threads
|
cmp-lg cs.CL
|
In this paper we will present our ongoing work on a plan-based discourse
processor developed in the context of the Enthusiast Spanish to English
translation system as part of the JANUS multi-lingual speech-to-speech
translation system. We will demonstrate that theories of discourse which
postulate a strict tree structure of discourse on either the intentional or
attentional level are not totally adequate for handling spontaneous dialogues.
We will present our extension to this approach along with its implementation in
our plan-based discourse processor. We will demonstrate that the implementation
of our approach outperforms an implementation based on the strict tree
structure approach.
|
cmp-lg/9504026
|
The intersection of Finite State Automata and Definite Clause Grammars
|
cmp-lg cs.CL
|
Bernard Lang defines parsing as the calculation of the intersection of a FSA
(the input) and a CFG. Viewing the input for parsing as a FSA rather than as a
string combines well with some approaches in speech understanding systems, in
which parsing takes a word lattice as input (rather than a word string).
Furthermore, certain techniques for robust parsing can be modelled as finite
state transducers. In this paper we investigate how we can generalize this
approach for unification grammars. In particular we will concentrate on how we
might the calculation of the intersection of a FSA and a DCG. It is shown that
existing parsing algorithms can be easily extended for FSA inputs. However, we
also show that the termination properties change drastically: we show that it
is undecidable whether the intersection of a FSA and a DCG is empty (even if
the DCG is off-line parsable). Furthermore we discuss approaches to cope with
the problem.
|
cmp-lg/9504027
|
An Efficient Generation Algorithm for Lexicalist MT
|
cmp-lg cs.CL
|
The lexicalist approach to Machine Translation offers significant advantages
in the development of linguistic descriptions. However, the Shake-and-Bake
generation algorithm of (Whitelock, COLING-92) is NP-complete. We present a
polynomial time algorithm for lexicalist MT generation provided that sufficient
information can be transferred to ensure more determinism.
|
cmp-lg/9504028
|
Memoization of Coroutined Constraints
|
cmp-lg cs.CL
|
Some linguistic constraints cannot be effectively resolved during parsing at
the location in which they are most naturally introduced. This paper shows how
constraints can be propagated in a memoizing parser (such as a chart parser) in
much the same way that variable bindings are, providing a general treatment of
constraint coroutining in memoization. Prolog code for a simple application of
our technique to Bouma and van Noord's (1994) categorial grammar analysis of
Dutch is provided.
|
cmp-lg/9504029
|
Quantifiers, Anaphora, and Intensionality
|
cmp-lg cs.CL
|
The relationship between Lexical-Functional Grammar (LFG) {\em functional
structures} (f-structures) for sentences and their semantic interpretations can
be expressed directly in a fragment of linear logic in a way that correctly
explains the constrained interactions between quantifier scope ambiguity, bound
anaphora and intensionality. This deductive approach to semantic interpretaion
obviates the need for additional mechanisms, such as Cooper storage, to
represent the possible scopes of a quantified NP, and explains the interactions
between quantified NPs, anaphora and intensional verbs such as `seek'. A single
specification in linear logic of the argument requirements of intensional verbs
is sufficient to derive the correct reading predictions for intensional-verb
clauses both with nonquantified and with quantified direct objects. In
particular, both de dicto and de re readings are derived for quantified
objects. The effects of type-raising or quantifying-in rules in other
frameworks here just follow as linear-logic theorems.
While our approach resembles current categorial approaches in important ways,
it differs from them in allowing the greater type flexibility of categorial
semantics while maintaining a precise connection to syntax. As a result, we are
able to provide derivations for certain readings of sentences with intensional
verbs and complex direct objects that are not derivable in current purely
categorial accounts of the syntax-semantics interface.
|
cmp-lg/9504030
|
Statistical Decision-Tree Models for Parsing
|
cmp-lg cs.CL
|
Syntactic natural language parsers have shown themselves to be inadequate for
processing highly-ambiguous large-vocabulary text, as is evidenced by their
poor performance on domains like the Wall Street Journal, and by the movement
away from parsing-based approaches to text-processing in general. In this
paper, I describe SPATTER, a statistical parser based on decision-tree learning
techniques which constructs a complete parse for every sentence and achieves
accuracy rates far better than any published result. This work is based on the
following premises: (1) grammars are too complex and detailed to develop
manually for most interesting domains; (2) parsing models must rely heavily on
lexical and contextual information to analyze sentences accurately; and (3)
existing {$n$}-gram modeling techniques are inadequate for parsing models. In
experiments comparing SPATTER with IBM's computer manuals parser, SPATTER
significantly outperforms the grammar-based parser. Evaluating SPATTER against
the Penn Treebank Wall Street Journal corpus using the PARSEVAL measures,
SPATTER achieves 86\% precision, 86\% recall, and 1.3 crossing brackets per
sentence for sentences of 40 words or less, and 91\% precision, 90\% recall,
and 0.5 crossing brackets for sentences between 10 and 20 words in length.
|
cmp-lg/9504031
|
Error-tolerant Finite State Recognition with Applications to
Morphological Analysis and Spelling Correction
|
cmp-lg cs.CL
|
Error-tolerant recognition enables the recognition of strings that deviate
mildly from any string in the regular set recognized by the underlying finite
state recognizer. Such recognition has applications in error-tolerant
morphological processing, spelling correction, and approximate string matching
in information retrieval. After a description of the concepts and algorithms
involved, we give examples from two applications: In the context of
morphological analysis, error-tolerant recognition allows misspelled input word
forms to be corrected, and morphologically analyzed concurrently. We present an
application of this to error-tolerant analysis of agglutinative morphology of
Turkish words. The algorithm can be applied to morphological analysis of any
language whose morphology is fully captured by a single (and possibly very
large) finite state transducer, regardless of the word formation processes and
morphographemic phenomena involved. In the context of spelling correction,
error-tolerant recognition can be used to enumerate correct candidate forms
from a given misspelled string within a certain edit distance. Again, it can be
applied to any language with a word list comprising all inflected forms, or
whose morphology is fully described by a finite state transducer. We present
experimental results for spelling correction for a number of languages. These
results indicate that such recognition works very efficiently for candidate
generation in spelling correction for many European languages such as English,
Dutch, French, German, Italian (and others) with very large word lists of root
and inflected forms (some containing well over 200,000 forms), generating all
candidate solutions within 10 to 45 milliseconds (with edit distance 1) on a
SparcStation 10/41. For spelling correction in Turkish, error-tolerant
|
cmp-lg/9504032
|
The Replace Operator
|
cmp-lg cs.CL
|
This paper introduces to the calculus of regular expressions a replace
operator, ->, and defines a set of replacement expressions that concisely
encode several alternate variations of the operation.
The basic case is unconditional obligatory replacement:
UPPER -> LOWER
Conditional versions of replacement, such as,
UPPER -> LOWER || LEFT _ RIGHT constrain the operation by left and right
contexts. UPPER, LOWER, LEFT, and RIGHT may be regular expressions of any
complexity.
Replace expressions denote regular relations. The replace operator is defined
in terms of other regular expression operators using techniques introduced by
Ronald M. Kaplan and Martin Kay in "Regular Models of Phonological Rule
Systems" (Computational Linguistics 20:3 331-378. 1994).
|
cmp-lg/9504033
|
Corpus Statistics Meet the Noun Compound: Some Empirical Results
|
cmp-lg cs.CL
|
A variety of statistical methods for noun compound analysis are implemented
and compared. The results support two main conclusions. First, the use of
conceptual association not only enables a broad coverage, but also improves the
accuracy. Second, an analysis model based on dependency grammar is
substantially more accurate than one based on deepest constituents, even though
the latter is more prevalent in the literature.
|
cmp-lg/9504034
|
Bayesian Grammar Induction for Language Modeling
|
cmp-lg cs.CL
|
We describe a corpus-based induction algorithm for probabilistic context-free
grammars. The algorithm employs a greedy heuristic search within a Bayesian
framework, and a post-pass using the Inside-Outside algorithm. We compare the
performance of our algorithm to n-gram models and the Inside-Outside algorithm
in three language modeling tasks. In two of the tasks, the training data is
generated by a probabilistic context-free grammar and in both tasks our
algorithm outperforms the other techniques. The third task involves
naturally-occurring data, and in this task our algorithm does not perform as
well as n-gram models but vastly outperforms the Inside-Outside algorithm.
|
cmp-lg/9505001
|
Response Generation in Collaborative Negotiation
|
cmp-lg cs.CL
|
In collaborative planning activities, since the agents are autonomous and
heterogeneous, it is inevitable that conflicts arise in their beliefs during
the planning process. In cases where such conflicts are relevant to the task at
hand, the agents should engage in collaborative negotiation as an attempt to
square away the discrepancies in their beliefs. This paper presents a
computational strategy for detecting conflicts regarding proposed beliefs and
for engaging in collaborative negotiation to resolve the conflicts that warrant
resolution. Our model is capable of selecting the most effective aspect to
address in its pursuit of conflict resolution in cases where multiple conflicts
arise, and of selecting appropriate evidence to justify the need for such
modification. Furthermore, by capturing the negotiation process in a recursive
Propose-Evaluate-Modify cycle of actions, our model can successfully handle
embedded negotiation subdialogues.
|
cmp-lg/9505002
|
New Techniques for Context Modeling
|
cmp-lg cs.CL
|
We introduce three new techniques for statistical language models: extension
modeling, nonmonotonic contexts, and the divergence heuristic. Together these
techniques result in language models that have few states, even fewer
parameters, and low message entropies. For example, our techniques achieve a
message entropy of 1.97 bits/char on the Brown corpus using only 89,325
parameters. In contrast, the character 4-gram model requires more than 250
times as many parameters in order to achieve a message entropy of only 2.47
bits/char. The fact that our model performs significantly better while using
vastly fewer parameters indicates that it is a better probability model of
natural language text.
|
cmp-lg/9505003
|
Compiling HPSG type constraints into definite clause programs
|
cmp-lg cs.CL
|
We present a new approach to HPSG processing: compiling HPSG grammars
expressed as type constraints into definite clause programs. This provides a
clear and computationally useful correspondence between linguistic theories and
their implementation. The compiler performs off-line constraint inheritance and
code optimization. As a result, we are able to efficiently process with HPSG
grammars without having to hand-translate them into definite clause or phrase
structure based systems.
|
cmp-lg/9505004
|
DATR Theories and DATR Models
|
cmp-lg cs.CL
|
Evans and Gazdar introduced DATR as a simple, non-monotonic language for
representing natural language lexicons. Although a number of implementations of
DATR exist, the full language has until now lacked an explicit, declarative
semantics. This paper rectifies the situation by providing a mathematical
semantics for DATR. We present a view of DATR as a language for defining
certain kinds of partial functions by cases. The formal model provides a
transparent treatment of DATR's notion of global context. It is shown that
DATR's default mechanism can be accounted for by interpreting value descriptors
as families of values indexed by paths.
|
cmp-lg/9505005
|
Learning Syntactic Rules and Tags with Genetic Algorithms for
Information Retrieval and Filtering: An Empirical Basis for Grammatical Rules
|
cmp-lg cs.CL
|
The grammars of natural languages may be learned by using genetic algorithms
that reproduce and mutate grammatical rules and part-of-speech tags, improving
the quality of later generations of grammatical components. Syntactic rules are
randomly generated and then evolve; those rules resulting in improved parsing
and occasionally improved retrieval and filtering performance are allowed to
further propagate. The LUST system learns the characteristics of the language
or sublanguage used in document abstracts by learning from the document
rankings obtained from the parsed abstracts. Unlike the application of
traditional linguistic rules to retrieval and filtering applications, LUST
develops grammatical structures and tags without the prior imposition of some
common grammatical assumptions (e.g., part-of-speech assumptions), producing
grammars that are empirically based and are optimized for this particular
application.
|
cmp-lg/9505006
|
Treating Coordination with Datalog Grammars
|
cmp-lg cs.CL
|
In previous work we studied a new type of DCGs, Datalog grammars, which are
inspired on database theory. Their efficiency was shown to be better than that
of their DCG counterparts under (terminating) OLDT-resolution. In this article
we motivate a variant of Datalog grammars which allows us a meta-grammatical
treatment of coordination. This treatment improves in some respects over
previous work on coordination in logic grammars, although more research is
needed for testing it in other respects.
|
cmp-lg/9505007
|
Parsing a Flexible Word Order Language
|
cmp-lg cs.CL
|
A logic formalism is presented which increases the expressive power of the
ID/LP format of GPSG by enlarging the inventory of ordering relations and
extending the domain of their application to non-siblings. This allows a
concise, modular and declarative statement of intricate word order
regularities.
|
cmp-lg/9505008
|
Conciseness through Aggregation in Text Generation
|
cmp-lg cs.CL
|
Aggregating different pieces of similar information is necessary to generate
concise and easy to understand reports in technical domains. This paper
presents a general algorithm that combines similar messages in order to
generate one or more coherent sentences for them. The process is not as trivial
as might be expected. Problems encountered are briefly described.
|
cmp-lg/9505009
|
Compilation of HPSG to TAG
|
cmp-lg cs.CL
|
We present an implemented compilation algorithm that translates HPSG into
lexicalized feature-based TAG, relating concepts of the two theories. While
HPSG has a more elaborated principle-based theory of possible phrase
structures, TAG provides the means to represent lexicalized structures more
explicitly. Our objectives are met by giving clear definitions that determine
the projection of structures from the lexicon, and identify maximal
projections, auxiliary trees and foot nodes.
|
cmp-lg/9505010
|
Tagset Reduction Without Information Loss
|
cmp-lg cs.CL
|
A technique for reducing a tagset used for n-gram part-of-speech
disambiguation is introduced and evaluated in an experiment. The technique
ensures that all information that is provided by the original tagset can be
restored from the reduced one. This is crucial, since we are interested in the
linguistically motivated tags for part-of-speech disambiguation. The reduced
tagset needs fewer parameters for its statistical model and allows more
accurate parameter estimation. Additionally, there is a slight but not
significant improvement of tagging accuracy.
|
cmp-lg/9505011
|
Evaluation of Semantic Clusters
|
cmp-lg cs.CL
|
Semantic clusters of a domain form an important feature that can be useful
for performing syntactic and semantic disambiguation. Several attempts have
been made to extract the semantic clusters of a domain by probabilistic or
taxonomic techniques. However, not much progress has been made in evaluating
the obtained semantic clusters. This paper focuses on an evaluation mechanism
that can be used to evaluate semantic clusters produced by a system against
those provided by human experts.
|
cmp-lg/9505012
|
A Symbolic and Surgical Acquisition of Terms through Variation
|
cmp-lg cs.CL
|
Terminological acquisition is an important issue in learning for NLP due to
the constant terminological renewal through technological changes. Terms play a
key role in several NLP-activities such as machine translation, automatic
indexing or text understanding. In opposition to classical once-and-for-all
approaches, we propose an incremental process for terminological enrichment
which operates on existing reference lists and large corpora. Candidate terms
are acquired by extracting variants of reference terms through {\em FASTR}, a
unification-based partial parser. As acquisition is performed within specific
morpho-syntactic contexts (coordinations, insertions or permutations of
compounds), rich conceptual links are learned together with candidate terms. A
clustering of terms related through coordination yields classes of conceptually
close terms while graphs resulting from insertions denote generic/specific
relations. A graceful degradation of the volume of acquisition on partial
initial lists confirms the robustness of the method to incomplete data.
|
cmp-lg/9505013
|
Utilizing Statistical Dialogue Act Processing in Verbmobil
|
cmp-lg cs.CL
|
In this paper, we present a statistical approach for dialogue act processing
in the dialogue component of the speech-to-speech translation system \vm.
Statistics in dialogue processing is used to predict follow-up dialogue acts.
As an application example we show how it supports repair when unexpected
dialogue states occur.
|
cmp-lg/9505014
|
Compositionality for Presuppositions over Tableaux
|
cmp-lg cs.CL
|
Tableaux originate as a decision method for a logical language. They can also
be extended to obtain a structure that spells out all the information in a set
of sentences in terms of truth value assignments to atomic formulas that appear
in them. This approach is pursued here. Over such a structure, compositional
rules are provided for obtaining the presuppositions of a logical statement
from its atomic subformulas and their presuppositions. The rules are based on
classical logic semantics and they are shown to model the behaviour of
presuppositions observed in natural language sentences built with {\em if
\ldots then}, {\em and} and {\em or}. The advantages of this method over
existing frameworks for presuppositions are discussed.
|
cmp-lg/9505015
|
Efficient Analysis of Complex Diagrams using Constraint-Based Parsing
|
cmp-lg cs.CL
|
This paper describes substantial advances in the analysis (parsing) of
diagrams using constraint grammars. The addition of set types to the grammar
and spatial indexing of the data make it possible to efficiently parse real
diagrams of substantial complexity. The system is probably the first to
demonstrate efficient diagram parsing using grammars that easily be retargeted
to other domains. The work assumes that the diagrams are available as a flat
collection of graphics primitives: lines, polygons, circles, Bezier curves and
text. This is appropriate for future electronic documents or for vectorized
diagrams converted from scanned images. The classes of diagrams that we have
analyzed include x,y data graphs and genetic diagrams drawn from the biological
literature, as well as finite state automata diagrams (states and arcs). As an
example, parsing a four-part data graph composed of 133 primitives required 35
sec using Macintosh Common Lisp on a Macintosh Quadra 700.
|
cmp-lg/9505016
|
A Pattern Matching method for finding Noun and Proper Noun Translations
from Noisy Parallel Corpora
|
cmp-lg cs.CL
|
We present a pattern matching method for compiling a bilingual lexicon of
nouns and proper nouns from unaligned, noisy parallel texts of
Asian/Indo-European language pairs. Tagging information of one language is
used. Word frequency and position information for high and low frequency words
are represented in two different vector forms for pattern matching. New anchor
point finding and noise elimination techniques are introduced. We obtained a
73.1\% precision. We also show how the results can be used in the compilation
of domain-specific noun phrases.
|
cmp-lg/9505017
|
Robust Parsing of Spoken Dialogue Using Contextual Knowledge and
Recognition Probabilities
|
cmp-lg cs.CL
|
In this paper we describe the linguistic processor of a spoken dialogue
system. The parser receives a word graph from the recognition module as its
input. Its task is to find the best path through the graph. If no complete
solution can be found, a robust mechanism for selecting multiple partial
results is applied. We show how the information content rate of the results can
be improved if the selection is based on an integrated quality score combining
word recognition scores and context-dependent semantic predictions. Results of
parsing word graphs with and without predictions are reported.
|
cmp-lg/9505018
|
Acquiring a Lexicon from Unsegmented Speech
|
cmp-lg cs.CL
|
We present work-in-progress on the machine acquisition of a lexicon from
sentences that are each an unsegmented phone sequence paired with a primitive
representation of meaning. A simple exploratory algorithm is described, along
with the direction of current work and a discussion of the relevance of the
problem for child language acquisition and computer speech recognition.
|
cmp-lg/9505019
|
Measuring semantic complexity
|
cmp-lg cs.CL
|
We define {\em semantic complexity} using a new concept of {\em meaning
automata}. We measure the semantic complexity of understanding of prepositional
phrases, of an "in depth understanding system", and of a natural language
interface to an on-line calendar. We argue that it is possible to measure some
semantic complexities of natural language processing systems before building
them, and that systems that exhibit relatively complex behavior can be built
from semantically simple components.
|
cmp-lg/9505020
|
CRYSTAL: Inducing a Conceptual Dictionary
|
cmp-lg cs.CL
|
One of the central knowledge sources of an information extraction system is a
dictionary of linguistic patterns that can be used to identify the conceptual
content of a text. This paper describes CRYSTAL, a system which automatically
induces a dictionary of "concept-node definitions" sufficient to identify
relevant information from a training corpus. Each of these concept-node
definitions is generalized as far as possible without producing errors, so that
a minimum number of dictionary entries cover the positive training instances.
Because it tests the accuracy of each proposed definition, CRYSTAL can often
surpass human intuitions in creating reliable extraction rules.
|
cmp-lg/9505021
|
Improving the Efficiency of a Generation Algorithm for Shake and Bake
Machine Translation Using Head-Driven Phrase Structure Grammar
|
cmp-lg cs.CL
|
A Shake and Bake machine translation algorithm for Head-Driven Phrase
Structure Grammar is introduced based on the algorithm proposed by Whitelock
for unification categorial grammar. The translation process is then analysed to
determine where the potential sources of inefficiency reside, and some
proposals are introduced which greatly improve the efficiency of the generation
algorithm. Preliminary empirical results from tests involving a small grammar
are presented, and suggestions for greater improvement to the algorithm are
provided.
|
cmp-lg/9505022
|
Generating One-Anaphoric Expressions: Where Does the Decision Lie?
|
cmp-lg cs.CL
|
Most natural language generation systems embody mechanisms for choosing
whether to subsequently refer to an already-introduced entity by means of a
pronoun or a definite noun phrase. Relatively few systems, however, consider
referring to entites by means of one-anaphoric expressions such as
\lingform{the small green one}. This paper looks at what is involved in
generating referring expressions of this type. Consideration of how to fit this
capability into a standard algorithm for referring expression generation leads
us to suggest a revision of some of the assumptions that underlie existing
approaches. We demonstrate the usefulness of our approach to one-anaphora
generation in the context of a simple database interface application, and make
some observations about the impact of this approach on referring expression
generation more generally.
|
cmp-lg/9505023
|
Some Novel Applications of Explanation-Based Learning to Parsing
Lexicalized Tree-Adjoining Grammars
|
cmp-lg cs.CL
|
In this paper we present some novel applications of Explanation-Based
Learning (EBL) technique to parsing Lexicalized Tree-Adjoining grammars. The
novel aspects are (a) immediate generalization of parses in the training set,
(b) generalization over recursive structures and (c) representation of
generalized parses as Finite State Transducers. A highly impoverished parser
called a ``stapler'' has also been introduced. We present experimental results
using EBL for different corpora and architectures to show the effectiveness of
our approach.
|
cmp-lg/9505024
|
Exploring the role of Punctuation in Parsing Natural Text
|
cmp-lg cs.CL
|
Few, if any, current NLP systems make any significant use of punctuation.
Intuitively, a treatment of punctuation seems necessary to the analysis and
production of text. Whilst this has been suggested in the fields of discourse
structure, it is still unclear whether punctuation can help in the syntactic
field. This investigation attempts to answer this question by parsing some
corpus-based material with two similar grammars --- one including rules for
punctuation, the other ignoring it. The punctuated grammar significantly
out-performs the unpunctuated one, and so the conclusion is that punctuation
can play a useful role in syntactic processing.
|
cmp-lg/9505025
|
Combining Multiple Knowledge Sources for Discourse Segmentation
|
cmp-lg cs.CL
|
We predict discourse segment boundaries from linguistic features of
utterances, using a corpus of spoken narratives as data. We present two methods
for developing segmentation algorithms from training data: hand tuning and
machine learning. When multiple types of features are used, results approach
human performance on an independent test set (both methods), and using
cross-validation (machine learning).
|
cmp-lg/9505026
|
Tagging the Teleman Corpus
|
cmp-lg cs.CL
|
Experiments were carried out comparing the Swedish Teleman and the English
Susanne corpora using an HMM-based and a novel reductionistic statistical
part-of-speech tagger. They indicate that tagging the Teleman corpus is the
more difficult task, and that the performance of the two different taggers is
comparable.
|
cmp-lg/9505027
|
Quantifier Scope and Constituency
|
cmp-lg cs.CL
|
Traditional approaches to quantifier scope typically need stipulation to
exclude readings that are unavailable to human understanders. This paper shows
that quantifier scope phenomena can be precisely characterized by a semantic
representation constrained by surface constituency, if the distinction between
referential and quantificational NPs is properly observed. A CCG implementation
is described and compared to other approaches.
|
cmp-lg/9505028
|
D-Tree Grammars
|
cmp-lg cs.CL
|
DTG are designed to share some of the advantages of TAG while overcoming some
of its limitations. DTG involve two composition operations called subsertion
and sister-adjunction. The most distinctive feature of DTG is that, unlike TAG,
there is complete uniformity in the way that the two DTG operations relate
lexical items: subsertion always corresponds to complementation and
sister-adjunction to modification. Furthermore, DTG, unlike TAG, can provide a
uniform analysis for em wh-movement in English and Kashmiri, despite the fact
that the em wh element in Kashmiri appears in sentence-second position, and not
sentence-initial position as in English.
|
cmp-lg/9505029
|
Mapping Scrambled Korean Sentences into English Using Synchronous TAGs
|
cmp-lg cs.CL
|
Synchronous Tree Adjoining Grammars can be used for Machine Translation.
However, translating a free order language such as Korean to English is
complicated. I present a mechanism to translate scrambled Korean sentences into
English by combining the concepts of Multi-Component TAGs (MC-TAGs) and
Synchronous TAGs (STAGs).
|
cmp-lg/9505030
|
Encoding Lexicalized Tree Adjoining Grammars with a Nonmonotonic
Inheritance Hierarchy
|
cmp-lg cs.CL
|
This paper shows how DATR, a widely used formal language for lexical
knowledge representation, can be used to define an LTAG lexicon as an
inheritance hierarchy with internal lexical rules. A bottom-up featural
encoding is used for LTAG trees and this allows lexical rules to be implemented
as covariation constraints within feature structures. Such an approach
eliminates the considerable redundancy otherwise associated with an LTAG
lexicon.
|
cmp-lg/9505031
|
The Compactness of Construction Grammars
|
cmp-lg cs.CL
|
We present an argument for {\em construction grammars} based on the minimum
description length (MDL) principle (a formal version of the Ockham Razor). The
argument consists in using linguistic and computational evidence in setting up
a formal model, and then applying the MDL principle to prove its superiority
with respect to alternative models. We show that construction-based
representations are at least an order of magnitude more compact that the
corresponding lexicalized representations of the same linguistic data.
The result is significant for our understanding of the relationship between
syntax and semantics, and consequently for choosing NLP architectures. For
instance, whether the processing should proceed in a pipeline from syntax to
semantics to pragmatics, and whether all linguistic information should be
combined in a set of constraints. From a broader perspective, this paper does
not only argue for a certain model of processing, but also provides a
methodology for determining advantages of different approaches to NLP.
|
cmp-lg/9505032
|
Context and ontology in understanding of dialogs
|
cmp-lg cs.CL
|
We present a model of NLP in which ontology and context are directly included
in a grammar. The model is based on the concept of {\em construction},
consisting of a set of features of form, a set of semantic and pragmatic
conditions describing its application context, and a description of its
meaning. In this model ontology is embedded into the grammar; e.g. the
hierarchy of {\it np} constructions is based on the corresponding ontology.
Ontology is also used in defining contextual parameters; e.g. $\left[
current\_question \ time(\_) \right] $.
A parser based on this model allowed us to build a set of dialog
understanding systems that include an on-line calendar, a banking machine, and
an insurance quote system. The proposed approach is an alternative to the
standard "pipeline" design of morphology-syntax-semantics-pragmatics; the
account of meaning conforms to our intuitions about compositionality, but there
is no homomorphism from syntax to semantics.
|
cmp-lg/9505033
|
User-Defined Nonmonotonicity in Unification-Based Formalisms
|
cmp-lg cs.CL
|
A common feature of recent unification-based grammar formalisms is that they
give the user the ability to define his own structures. However, this
possibility is mostly limited and does not include nonmonotonic operations. In
this paper we show how nonmonotonic operations can also be user-defined by
applying default logic (Reiter 1980) and generalizing previous results on
nonmonotonic sorts (Young & Rounds 1993).
|
cmp-lg/9505034
|
Semantic Ambiguity and Perceived Ambiguity
|
cmp-lg cs.CL
|
I explore some of the issues that arise when trying to establish a connection
between the underspecification hypothesis pursued in the NLP literature and
work on ambiguity in semantics and in the psychological literature. A theory of
underspecification is developed `from the first principles', i.e., starting
from a definition of what it means for a sentence to be semantically ambiguous
and from what we know about the way humans deal with ambiguity. An
underspecified language is specified as the translation language of a grammar
covering sentences that display three classes of semantic ambiguity: lexical
ambiguity, scopal ambiguity, and referential ambiguity. The expressions of this
language denote sets of senses. A formalization of defeasible reasoning with
underspecified representations is presented, based on Default Logic. Some
issues to be confronted by such a formalization are discussed.
|
cmp-lg/9505035
|
Development of a Spanish Version of the Xerox Tagger
|
cmp-lg cs.CL
|
This paper describes work performed withing the CRATER ({\em C}orpus {\em
R}esources {\em A}nd {\em T}erminology {\em E}xt{\em R}action, MLAP-93/20)
project, funded by the Commission of the European Communities. In particular,
it addresses the issue of adapting the Xerox Tagger to Spanish in order to tag
the Spanish version of the ITU (International Telecommunications Union) corpus.
The model implemented by this tagger is briefly presented along with some
modifications performed on it in order to use some parameters not
probabilistically estimated. Initial decisions, like the tagset, the lexicon
and the training corpus are also discussed. Finally, results are presented and
the benefits of the {\em mixed model} justified.
|
cmp-lg/9505036
|
Integrating Gricean and Attentional Constraints
|
cmp-lg cs.CL
|
This paper concerns how to generate and understand discourse anaphoric noun
phrases. I present the results of an analysis of all discourse anaphoric noun
phrases (N=1,233) in a corpus of ten narrative monologues, where the choice
between a definite pronoun or phrasal NP conforms largely to Gricean
constraints on informativeness. I discuss Dale and Reiter's [To appear] recent
model and show how it can be augmented for understanding as well as generating
the range of data presented here. I argue that integrating centering [Grosz et
al., 1983] [Kameyama, 1985] with this model can be applied uniformly to
discourse anaphoric pronouns and phrasal NPs. I conclude with a hypothesis for
addressing the interaction between local and global discourse processing.
|
cmp-lg/9505037
|
Identifying Word Translations in Non-Parallel Texts
|
cmp-lg cs.CL
|
Common algorithms for sentence and word-alignment allow the automatic
identification of word translations from parallel texts. This study suggests
that the identification of word translations should also be possible with
non-parallel and even unrelated texts. The method proposed is based on the
assumption that there is a correlation between the patterns of word
co-occurrences in texts of different languages.
|
cmp-lg/9505038
|
Ubiquitous Talker: Spoken Language Interaction with Real World Objects
|
cmp-lg cs.CL
|
Augmented reality is a research area that tries to embody an electronic
information space within the real world, through computational devices. A
crucial issue within this area, is the recognition of real world objects or
situations.
In natural language processing, it is much easier to determine
interpretations of utterances, even if they are ill-formed, when the context or
situation is fixed. We therefore introduce robust, natural language processing
into a system of augmented reality with situation awareness. Based on this
idea, we have developed a portable system, called the Ubiquitous Talker. This
consists of an LCD display that reflects the scene at which a user is looking
as if it is a transparent glass, a CCD camera for recognizing real world
objects with color-bar ID codes, a microphone for recognizing a human voice and
a speaker which outputs a synthesized voice. The Ubiquitous Talker provides its
user with some information related to a recognized object, by using the display
and voice. It also accepts requests or questions as voice inputs. The user
feels as if he/she is talking with the object itself through the system.
|
cmp-lg/9505039
|
Generating efficient belief models for task-oriented dialogues
|
cmp-lg cs.CL
|
We have shown that belief modelling for dialogue can be simplified if the
assumption is made that the participants are cooperating, i.e., they are not
committed to any goals requiring deception. In such domains, there is no need
to maintain individual representations of deeply nested beliefs; instead, three
specific types of belief can be used to summarize all the states of nested
belief that can exist about a domain entity.
Here, we set out to design a ``compiler'' for belief models. This system will
accept as input a description of agents' interactions with a task domain
expressed in a fully-expressive belief logic with non-monotonic and temporal
extensions. It generates an operational belief model for use in that domain,
sufficient for the requirements of cooperative dialogue, including the
negotiation of complex domain plans. The compiled model incorporates the belief
simplification mentioned above, and also uses a simplified temporal logic of
belief based on the restricted circumstances under which beliefs can change.
We shall review the motivation for creating such a system, and introduce a
general procedure for taking a logical specification for a domain and procesing
it into an operational model. We shall then discuss the specific changes that
are made during this procedure for limiting the level of abstraction at which
the concepts of belief nesting, default reasoning and time are expressed.
Finally we shall go through a worked example relating to the Map Task, a simple
cooperative problem-solving exercise.
|
cmp-lg/9505040
|
Text Chunking using Transformation-Based Learning
|
cmp-lg cs.CL
|
Eric Brill introduced transformation-based learning and showed that it can do
part-of-speech tagging with fairly high accuracy. The same method can be
applied at a higher level of textual interpretation for locating chunks in the
tagged text, including non-recursive ``baseNP'' chunks. For this purpose, it is
convenient to view chunking as a tagging problem by encoding the chunk
structure in new tags attached to each word. In automatic tests using
Treebank-derived data, this technique achieved recall and precision rates of
roughly 92% for baseNP chunks and 88% for somewhat more complex chunks that
partition the sentence. Some interesting adaptations to the
transformation-based learning approach are also suggested by this application.
|
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