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cmp-lg/9708013
explanation-based learning of data oriented parsing
cmp-lg cs.CL
This paper presents a new view of Explanation-Based Learning (EBL) of natural language parsing. Rather than employing EBL for specializing parsers by inferring new ones, this paper suggests employing EBL for learning how to reduce ambiguity only partially. The present method consists of an EBL algorithm for learnin...
cmp-lg/9709001
The Complexity of Recognition of Linguistically Adequate Dependency Grammars
cmp-lg cs.CL
Results of computational complexity exist for a wide range of phrase structure-based grammar formalisms, while there is an apparent lack of such results for dependency-based formalisms. We here adapt a result on the complexity of ID/LP-grammars to the dependency framework. Contrary to previous studies on heavily rest...
cmp-lg/9709002
Learning Methods for Combining Linguistic Indicators to Classify Verbs
cmp-lg cs.CL
Fourteen linguistically-motivated numerical indicators are evaluated for their ability to categorize verbs as either states or events. The values for each indicator are computed automatically across a corpus of text. To improve classification performance, machine learning techniques are employed to combine multiple i...
cmp-lg/9709003
Combining Multiple Methods for the Automatic Construction of Multilingual WordNets
cmp-lg cs.CL
This paper explores the automatic construction of a multilingual Lexical Knowledge Base from preexisting lexical resources. First, a set of automatic and complementary techniques for linking Spanish words collected from monolingual and bilingual MRDs to English WordNet synsets are described. Second, we show how resul...
cmp-lg/9709004
Integrating a Lexical Database and a Training Collection for Text Categorization
cmp-lg cs.CL
Automatic text categorization is a complex and useful task for many natural language processing applications. Recent approaches to text categorization focus more on algorithms than on resources involved in this operation. In contrast to this trend, we present an approach based on the integration of widely available r...
cmp-lg/9709005
A generation algorithm for f-structure representations
cmp-lg cs.CL
This paper shows that previously reported generation algorithms run into problems when dealing with f-structure representations. A generation algorithm that is suitable for this type of representations is presented: the Semantic Kernel Generation (SKG) algorithm. The SKG method has the same processing strategy as the...
cmp-lg/9709006
Semantic Processing of Out-Of-Vocabulary Words in a Spoken Dialogue System
cmp-lg cs.CL
One of the most important causes of failure in spoken dialogue systems is usually neglected: the problem of words that are not covered by the system's vocabulary (out-of-vocabulary or OOV words). In this paper a methodology is described for the detection, classification and processing of OOV words in an automatic tra...
cmp-lg/9709007
Using WordNet to Complement Training Information in Text Categorization
cmp-lg cs.CL
Automatic Text Categorization (TC) is a complex and useful task for many natural language applications, and is usually performed through the use of a set of manually classified documents, a training collection. We suggest the utilization of additional resources like lexical databases to increase the amount of informa...
cmp-lg/9709008
Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy
cmp-lg cs.CL
This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantified with the computa...
cmp-lg/9709009
Evaluating Parsing Schemes with Entropy Indicators
cmp-lg cs.CL
This paper introduces an objective metric for evaluating a parsing scheme. It is based on Shannon's original work with letter sequences, which can be extended to part-of-speech tag sequences. It is shown that this regular language is an inadequate model for natural language, but a representation is used that models l...
cmp-lg/9709010
Message-Passing Protocols for Real-World Parsing -- An Object-Oriented Model and its Preliminary Evaluation
cmp-lg cs.CL
We argue for a performance-based design of natural language grammars and their associated parsers in order to meet the constraints imposed by real-world NLP. Our approach incorporates declarative and procedural knowledge about language and language use within an object-oriented specification framework. We discuss sev...
cmp-lg/9709011
Off-line Parsability and the Well-foundedness of Subsumption
cmp-lg cs.CL
Typed feature structures are used extensively for the specification of linguistic information in many formalisms. The subsumption relation orders TFSs by their information content. We prove that subsumption of acyclic TFSs is well-founded, whereas in the presence of cycles general TFS subsumption is not well-founded....
cmp-lg/9709012
Using Single Layer Networks for Discrete, Sequential Data: An Example from Natural Language Processing
cmp-lg cs.CL
A natural language parser which has been successfully implemented is described. This is a hybrid system, in which neural networks operate within a rule based framework. It can be accessed via telnet for users to try on their own text. (For details, contact the author.) Tested on technical manuals, the parser finds th...
cmp-lg/9709013
An Abstract Machine for Unification Grammars
cmp-lg cs.CL
This work describes the design and implementation of an abstract machine, Amalia, for the linguistic formalism ALE, which is based on typed feature structures. This formalism is one of the most widely accepted in computational linguistics and has been used for designing grammars in various linguistic theories, most n...
cmp-lg/9709014
Amalia -- A Unified Platform for Parsing and Generation
cmp-lg cs.CL
Contemporary linguistic theories (in particular, HPSG) are declarative in nature: they specify constraints on permissible structures, not how such structures are to be computed. Grammars designed under such theories are, therefore, suitable for both parsing and generation. However, practical implementations of such t...
cmp-lg/9709015
Segmentation of Expository Texts by Hierarchical Agglomerative Clustering
cmp-lg cs.CL
We propose a method for segmentation of expository texts based on hierarchical agglomerative clustering. The method uses paragraphs as the basic segments for identifying hierarchical discourse structure in the text, applying lexical similarity between them as the proximity test. Linear segmentation can be induced fro...
cmp-lg/9710001
Use of Weighted Finite State Transducers in Part of Speech Tagging
cmp-lg cs.CL
This paper addresses issues in part of speech disambiguation using finite-state transducers and presents two main contributions to the field. One of them is the use of finite-state machines for part of speech tagging. Linguistic and statistical information is represented in terms of weights on transitions in weighted...
cmp-lg/9710002
Tagging French Without Lexical Probabilities -- Combining Linguistic Knowledge And Statistical Learning
cmp-lg cs.CL
This paper explores morpho-syntactic ambiguities for French to develop a strategy for part-of-speech disambiguation that a) reflects the complexity of French as an inflected language, b) optimizes the estimation of probabilities, c) allows the user flexibility in choosing a tagset. The problem in extracting lexical p...
cmp-lg/9710003
Disambiguating with Controlled Disjunctions
cmp-lg cs.CL
In this paper, we propose a disambiguating technique called controlled disjunctions. This extension of the so-called named disjunctions relies on the relations existing between feature values (covariation, control, etc.). We show that controlled disjunctions can implement different kind of ambiguities in a consistent...
cmp-lg/9710004
Parsing syllables: modeling OT computationally
cmp-lg cs.CL
In this paper, I propose to implement syllabification in OT as a parser. I propose several innovations that result in a finite and small candidate set. The candidate set problem is handled with several moves: i) MAX and DEP violations are not hypothesized by the parser, ii) candidates are encoded locally, and iii) EV...
cmp-lg/9710005
Attaching Multiple Prepositional Phrases: Generalized Backed-off Estimation
cmp-lg cs.CL
There has recently been considerable interest in the use of lexically-based statistical techniques to resolve prepositional phrase attachments. To our knowledge, however, these investigations have only considered the problem of attaching the first PP, i.e., in a [V NP PP] configuration. In this paper, we consider one...
cmp-lg/9710006
Learning Features that Predict Cue Usage
cmp-lg cs.CL
Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanations. Previous attempts to devise rules for text generation were based on intuition or small numbers of constructed examples. We apply a mach...
cmp-lg/9710007
A Corpus-Based Investigation of Definite Description Use
cmp-lg cs.CL
We present the results of a study of definite descriptions use in written texts aimed at assessing the feasibility of annotating corpora with information about definite description interpretation. We ran two experiments, in which subjects were asked to classify the uses of definite descriptions in a corpus of 33 news...
cmp-lg/9710008
Probabilistic Event Categorization
cmp-lg cs.CL
This paper describes the automation of a new text categorization task. The categories assigned in this task are more syntactically, semantically, and contextually complex than those typically assigned by fully automatic systems that process unseen test data. Our system for assigning these categories is a probabilisti...
cmp-lg/9711001
Probabilistic Constraint Logic Programming
cmp-lg cs.CL
This paper addresses two central problems for probabilistic processing models: parameter estimation from incomplete data and efficient retrieval of most probable analyses. These questions have been answered satisfactorily only for probabilistic regular and context-free models. We address these problems for a more exp...
cmp-lg/9711002
Approximating Context-Free Grammars with a Finite-State Calculus
cmp-lg cs.CL
Although adequate models of human language for syntactic analysis and semantic interpretation are of at least context-free complexity, for applications such as speech processing in which speed is important finite-state models are often preferred. These requirements may be reconciled by using the more complex grammar ...
cmp-lg/9711003
Probabilistic Parsing Using Left Corner Language Models
cmp-lg cs.CL
We introduce a novel parser based on a probabilistic version of a left-corner parser. The left-corner strategy is attractive because rule probabilities can be conditioned on both top-down goals and bottom-up derivations. We develop the underlying theory and explain how a grammar can be induced from analyzed data. We ...
cmp-lg/9711004
Variation and Synthetic Speech
cmp-lg cs.CL
We describe the approach to linguistic variation taken by the Motorola speech synthesizer. A pan-dialectal pronunciation dictionary is described, which serves as the training data for a neural network based letter-to-sound converter. Subsequent to dictionary retrieval or letter-to-sound generation, pronunciations are...
cmp-lg/9711005
Some apparently disjoint aims and requirements for grammar development environments: the case of natural language generation
cmp-lg cs.CL
Grammar development environments (GDE's) for analysis and for generation have not yet come together. Despite the fact that analysis-oriented GDE's (such as ALEP) may include some possibility of sentence generation, the development techniques and kinds of resources suggested are apparently not those required for pract...
cmp-lg/9711006
Contextual Information and Specific Language Models for Spoken Language Understanding
cmp-lg cs.CL
In this paper we explain how contextual expectations are generated and used in the task-oriented spoken language understanding system Dialogos. The hard task of recognizing spontaneous speech on the telephone may greatly benefit from the use of specific language models during the recognition of callers' utterances. B...
cmp-lg/9711007
Language Modelling For Task-Oriented Domains
cmp-lg cs.CL
This paper is focused on the language modelling for task-oriented domains and presents an accurate analysis of the utterances acquired by the Dialogos spoken dialogue system. Dialogos allows access to the Italian Railways timetable by using the telephone over the public network. The language modelling aspects of spec...
cmp-lg/9711008
On the use of expectations for detecting and repairing human-machine miscommunication
cmp-lg cs.CL
In this paper I describe how miscommunication problems are dealt with in the spoken language system DIALOGOS. The dialogue module of the system exploits dialogic expectations in a twofold way: to model what future user utterance might be about (predictions), and to account how the user's next utterance may be related...
cmp-lg/9711009
Towards an Improved Performance Measure for Language Models
cmp-lg cs.CL
In this paper a first attempt at deriving an improved performance measure for language models, the probability ratio measure (PRM) is described. In a proof of concept experiment, it is shown that PRM correlates better with recognition accuracy and can lead to better recognition results when used as the optimisation c...
cmp-lg/9711010
Application-driven automatic subgrammar extraction
cmp-lg cs.CL
The space and run-time requirements of broad coverage grammars appear for many applications unreasonably large in relation to the relative simplicity of the task at hand. On the other hand, handcrafted development of application-dependent grammars is in danger of duplicating work which is then difficult to re-use in ...
cmp-lg/9711011
The effect of alternative tree representations on tree bank grammars
cmp-lg cs.CL
The performance of PCFGs estimated from tree banks is sensitive to the particular way in which linguistic constructions are represented as trees in the tree bank. This paper presents a theoretical analysis of the effect of different tree representations for PP attachment on PCFG models, and introduces a new methodolo...
cmp-lg/9711012
Proof Nets and the Complexity of Processing Center-Embedded Constructions
cmp-lg cs.CL
This paper shows how proof nets can be used to formalize the notion of ``incomplete dependency'' used in psycholinguistic theories of the unacceptability of center-embedded constructions. Such theories of human language processing can usually be restated in terms of geometrical constraints on proof nets. The paper en...
cmp-lg/9711013
Features as Resources in R-LFG
cmp-lg cs.CL
This paper introduces a non-unification-based version of LFG called R-LFG (Resource-based Lexical Functional Grammar), which combines elements from both LFG and Linear Logic. The paper argues that a resource sensitive account provides a simpler treatment of many linguistic uses of non-monotonic devices in LFG, such a...
cmp-lg/9711014
Type-driven semantic interpretation and feature dependencies in R-LFG
cmp-lg cs.CL
Once one has enriched LFG's formal machinery with the linear logic mechanisms needed for semantic interpretation as proposed by Dalrymple et. al., it is natural to ask whether these make any existing components of LFG redundant. As Dalrymple and her colleagues note, LFG's f-structure completeness and coherence constr...
cmp-lg/9712001
Applying Explanation-based Learning to Control and Speeding-up Natural Language Generation
cmp-lg cs.CL
This paper presents a method for the automatic extraction of subgrammars to control and speeding-up natural language generation NLG. The method is based on explanation-based learning (EBL). The main advantage for the proposed new method for NLG is that the complexity of the grammatical decision making process during ...
cmp-lg/9712002
Machine Learning of User Profiles: Representational Issues
cmp-lg cs.CL cs.LG
As more information becomes available electronically, tools for finding information of interest to users becomes increasingly important. The goal of the research described here is to build a system for generating comprehensible user profiles that accurately capture user interest with minimum user interaction. The res...
cmp-lg/9712003
Context as a Spurious Concept
cmp-lg cs.CL
I take issue with AI formalizations of context, primarily the formalization by McCarthy and Buvac, that regard context as an undefined primitive whose formalization can be the same in many different kinds of AI tasks. In particular, any theory of context in natural language must take the special nature of natural lan...
cmp-lg/9712004
Multi-document Summarization by Graph Search and Matching
cmp-lg cs.CL
We describe a new method for summarizing similarities and differences in a pair of related documents using a graph representation for text. Concepts denoted by words, phrases, and proper names in the document are represented positionally as nodes in the graph along with edges corresponding to semantic relations betwe...
cmp-lg/9712005
Topic Graph Generation for Query Navigation: Use of Frequency Classes for Topic Extraction
cmp-lg cs.CL
To make an interactive guidance mechanism for document retrieval systems, we developed a user-interface which presents users the visualized map of topics at each stage of retrieval process. Topic words are automatically extracted by frequency analysis and the strength of the relationships between topic words is measu...
cmp-lg/9712006
"I don't believe in word senses"
cmp-lg cs.CL
Word sense disambiguation assumes word senses. Within the lexicography and linguistics literature, they are known to be very slippery entities. The paper looks at problems with existing accounts of `word sense' and describes the various kinds of ways in which a word's meaning can deviate from its core meaning. An ana...
cmp-lg/9712007
Foreground and Background Lexicons and Word Sense Disambiguation for Information Extraction
cmp-lg cs.CL
Lexicon acquisition from machine-readable dictionaries and corpora is currently a dynamic field of research, yet it is often not clear how lexical information so acquired can be used, or how it relates to structured meaning representations. In this paper I look at this issue in relation to Information Extraction (her...
cmp-lg/9712008
What is word sense disambiguation good for?
cmp-lg cs.CL
Word sense disambiguation has developed as a sub-area of natural language processing, as if, like parsing, it was a well-defined task which was a pre-requisite to a wide range of language-understanding applications. First, I review earlier work which shows that a set of senses for a word is only ever defined relative...
cmp-lg/9712009
Speech Repairs, Intonational Boundaries and Discourse Markers: Modeling Speakers' Utterances in Spoken Dialog
cmp-lg cs.CL
In this thesis, we present a statistical language model for resolving speech repairs, intonational boundaries and discourse markers. Rather than finding the best word interpretation for an acoustic signal, we redefine the speech recognition problem to so that it also identifies the POS tags, discourse markers, speech...
cmp-lg/9712010
Orthographic Structuring of Human Speech and Texts: Linguistic Application of Recurrence Quantification Analysis
cmp-lg cs.CL
A methodology based upon recurrence quantification analysis is proposed for the study of orthographic structure of written texts. Five different orthographic data sets (20th century Italian poems, 20th century American poems, contemporary Swedish poems with their corresponding Italian translations, Italian speech sam...
cmp-lg/9801001
Hierarchical Non-Emitting Markov Models
cmp-lg cs.CL
We describe a simple variant of the interpolated Markov model with non-emitting state transitions and prove that it is strictly more powerful than any Markov model. More importantly, the non-emitting model outperforms the classic interpolated model on the natural language texts under a wide range of experimental cond...
cmp-lg/9801002
Identifying Discourse Markers in Spoken Dialog
cmp-lg cs.CL
In this paper, we present a method for identifying discourse marker usage in spontaneous speech based on machine learning. Discourse markers are denoted by special POS tags, and thus the process of POS tagging can be used to identify discourse markers. By incorporating POS tagging into language modeling, discourse ma...
cmp-lg/9801003
Do not forget: Full memory in memory-based learning of word pronunciation
cmp-lg cs.CL
Memory-based learning, keeping full memory of learning material, appears a viable approach to learning NLP tasks, and is often superior in generalisation accuracy to eager learning approaches that abstract from learning material. Here we investigate three partial memory-based learning approaches which remove from mem...
cmp-lg/9801004
Modularity in inductively-learned word pronunciation systems
cmp-lg cs.CL
In leading morpho-phonological theories and state-of-the-art text-to-speech systems it is assumed that word pronunciation cannot be learned or performed without in-between analyses at several abstraction levels (e.g., morphological, graphemic, phonemic, syllabic, and stress levels). We challenge this assumption for t...
cmp-lg/9801005
A General, Sound and Efficient Natural Language Parsing Algorithm based on Syntactic Constraints Propagation
cmp-lg cs.CL
This paper presents a new context-free parsing algorithm based on a bidirectional strictly horizontal strategy which incorporates strong top-down predictions (derivations and adjacencies). From a functional point of view, the parser is able to propagate syntactic constraints reducing parsing ambiguity. From a compu...
cmp-lg/9802001
Look-Back and Look-Ahead in the Conversion of Hidden Markov Models into Finite State Transducers
cmp-lg cs.CL
This paper describes the conversion of a Hidden Markov Model into a finite state transducer that closely approximates the behavior of the stochastic model. In some cases the transducer is equivalent to the HMM. This conversion is especially advantageous for part-of-speech tagging because the resulting transducer can ...
cmp-lg/9802002
A Hybrid Environment for Syntax-Semantic Tagging
cmp-lg cs.CL
The thesis describes the application of the relaxation labelling algorithm to NLP disambiguation. Language is modelled through context constraint inspired on Constraint Grammars. The constraints enable the use of a real value statind "compatibility". The technique is applied to POS tagging, Shallow Parsing and Word S...
cmp-lg/9803001
Automating Coreference: The Role of Annotated Training Data
cmp-lg cs.CL
We report here on a study of interannotator agreement in the coreference task as defined by the Message Understanding Conference (MUC-6 and MUC-7). Based on feedback from annotators, we clarified and simplified the annotation specification. We then performed an analysis of disagreement among several annotators, concl...
cmp-lg/9803002
Time, Tense and Aspect in Natural Language Database Interfaces
cmp-lg cs.CL
Most existing natural language database interfaces (NLDBs) were designed to be used with database systems that provide very limited facilities for manipulating time-dependent data, and they do not support adequately temporal linguistic mechanisms (verb tenses, temporal adverbials, temporal subordinate clauses, etc.)....
cmp-lg/9803003
Nymble: a High-Performance Learning Name-finder
cmp-lg cs.CL
This paper presents a statistical, learned approach to finding names and other non-recursive entities in text (as per the MUC-6 definition of the NE task), using a variant of the standard hidden Markov model. We present our justification for the problem and our approach, a detailed discussion of the model itself and ...
cmp-lg/9804001
Graph Interpolation Grammars: a Rule-based Approach to the Incremental Parsing of Natural Languages
cmp-lg cs.CL
Graph Interpolation Grammars are a declarative formalism with an operational semantics. Their goal is to emulate salient features of the human parser, and notably incrementality. The parsing process defined by GIGs incrementally builds a syntactic representation of a sentence as each successive lexeme is read. A GIG ...
cmp-lg/9804002
The Proper Treatment of Optimality in Computational Phonology
cmp-lg cs.CL
This paper presents a novel formalization of optimality theory. Unlike previous treatments of optimality in computational linguistics, starting with Ellison (1994), the new approach does not require any explicit marking and counting of constraint violations. It is based on the notion of "lenient composition," defined...
cmp-lg/9804003
Treatment of Epsilon-Moves in Subset Construction
cmp-lg cs.CL
The paper discusses the problem of determinising finite-state automata containing large numbers of epsilon-moves. Experiments with finite-state approximations of natural language grammars often give rise to very large automata with a very large number of epsilon-moves. The paper identifies three subset construction a...
cmp-lg/9804004
Corpus-Based Word Sense Disambiguation
cmp-lg cs.CL
Resolution of lexical ambiguity, commonly termed ``word sense disambiguation'', is expected to improve the analytical accuracy for tasks which are sensitive to lexical semantics. Such tasks include machine translation, information retrieval, parsing, natural language understanding and lexicography. Reflecting the gro...
cmp-lg/9804005
On the existence of certain total recursive functions in nontrivial axiom systems, I
cmp-lg cs.CL
We investigate the existence of a class of ZFC-provably total recursive unary functions, given certain constraints, and apply some of those results to show that, for $\Sigma_1$-sound set theory, ZFC$\not\vdash P<NP$.
cmp-lg/9805001
Valence Induction with a Head-Lexicalized PCFG
cmp-lg cs.CL
This paper presents an experiment in learning valences (subcategorization frames) from a 50 million word text corpus, based on a lexicalized probabilistic context free grammar. Distributions are estimated using a modified EM algorithm. We evaluate the acquired lexicon both by comparison with a dictionary and by entro...
cmp-lg/9805002
Group Theory and Grammatical Description
cmp-lg cs.CL
This paper presents a model for linguistic description based on group theory. A grammar in this model, or "G-grammar", is a collection of lexical expressions which are products of logical forms, phonological forms, and their inverses. Phrasal descriptions are obtained by forming products of lexical expressions and by...
cmp-lg/9805003
Models of Co-occurrence
cmp-lg cs.CL
A model of co-occurrence in bitext is a boolean predicate that indicates whether a given pair of word tokens co-occur in corresponding regions of the bitext space. Co-occurrence is a precondition for the possibility that two tokens might be mutual translations. Models of co-occurrence are the glue that binds methods ...
cmp-lg/9805004
Annotation Style Guide for the Blinker Project
cmp-lg cs.CL
This annotation style guide was created by and for the Blinker project at the University of Pennsylvania. The Blinker project was so named after the ``bilingual linker'' GUI, which was created to enable bilingual annotators to ``link'' word tokens that are mutual translations in parallel texts. The parallel text chos...
cmp-lg/9805005
Manual Annotation of Translational Equivalence: The Blinker Project
cmp-lg cs.CL
Bilingual annotators were paid to link roughly sixteen thousand corresponding words between on-line versions of the Bible in modern French and modern English. These annotations are freely available to the research community from http://www.cis.upenn.edu/~melamed . The annotations can be used for several purposes. Fir...
cmp-lg/9805006
Word-to-Word Models of Translational Equivalence
cmp-lg cs.CL
Parallel texts (bitexts) have properties that distinguish them from other kinds of parallel data. First, most words translate to only one other word. Second, bitext correspondence is noisy. This article presents methods for biasing statistical translation models to reflect these properties. Analysis of the expected b...
cmp-lg/9805007
Parsing Inside-Out
cmp-lg cs.CL
The inside-outside probabilities are typically used for reestimating Probabilistic Context Free Grammars (PCFGs), just as the forward-backward probabilities are typically used for reestimating HMMs. I show several novel uses, including improving parser accuracy by matching parsing algorithms to evaluation criteria; s...
cmp-lg/9805008
A Descriptive Characterization of Tree-Adjoining Languages (Full Version)
cmp-lg cs.CL
Since the early Sixties and Seventies it has been known that the regular and context-free languages are characterized by definability in the monadic second-order theory of certain structures. More recently, these descriptive characterizations have been used to obtain complexity results for constraint- and principle-b...
cmp-lg/9805009
Discovery of Linguistic Relations Using Lexical Attraction
cmp-lg cs.CL
This work has been motivated by two long term goals: to understand how humans learn language and to build programs that can understand language. Using a representation that makes the relevant features explicit is a prerequisite for successful learning and understanding. Therefore, I chose to represent relations betwe...
cmp-lg/9805010
Integrating Text Plans for Conciseness and Coherence
cmp-lg cs.CL
Our experience with a critiquing system shows that when the system detects problems with the user's performance, multiple critiques are often produced. Analysis of a corpus of actual critiques revealed that even though each individual critique is concise and coherent, the set of critiques as a whole may exhibit sever...
cmp-lg/9805011
Automatic summarising: factors and directions
cmp-lg cs.CL
This position paper suggests that progress with automatic summarising demands a better research methodology and a carefully focussed research strategy. In order to develop effective procedures it is necessary to identify and respond to the context factors, i.e. input, purpose, and output factors, that bear on summari...
cmp-lg/9805012
Recognizing Syntactic Errors in the Writing of Second Language Learners
cmp-lg cs.CL
This paper reports on the recognition component of an intelligent tutoring system that is designed to help foreign language speakers learn standard English. The system models the grammar of the learner, with this instantiation of the system tailored to signers of American Sign Language (ASL). We discuss the theoretic...
cmp-lg/9806001
Learning Correlations between Linguistic Indicators and Semantic Constraints: Reuse of Context-Dependent Descriptions of Entities
cmp-lg cs.CL
This paper presents the results of a study on the semantic constraints imposed on lexical choice by certain contextual indicators. We show how such indicators are computed and how correlations between them and the choice of a noun phrase description of a named entity can be automatically established using supervised ...
cmp-lg/9806002
Computing Dialogue Acts from Features with Transformation-Based Learning
cmp-lg cs.CL
To interpret natural language at the discourse level, it is very useful to accurately recognize dialogue acts, such as SUGGEST, in identifying speaker intentions. Our research explores the utility of a machine learning method called Transformation-Based Learning (TBL) in computing dialogue acts, because TBL has a num...
cmp-lg/9806003
Lazy Transformation-Based Learning
cmp-lg cs.CL
We introduce a significant improvement for a relatively new machine learning method called Transformation-Based Learning. By applying a Monte Carlo strategy to randomly sample from the space of rules, rather than exhaustively analyzing all possible rules, we drastically reduce the memory and time costs of the algorit...
cmp-lg/9806004
Rationality, Cooperation and Conversational Implicature
cmp-lg cs.CL
Conversational implicatures are usually described as being licensed by the disobeying or flouting of a Principle of Cooperation. However, the specification of this principle has proved computationally elusive. In this paper we suggest that a more useful concept is rationality. Such a concept can be specified explicit...
cmp-lg/9806005
Eliminating deceptions and mistaken belief to infer conversational implicature
cmp-lg cs.CL
Conversational implicatures are usually described as being licensed by the disobeying or flouting of some principle by the speaker in cooperative dialogue. However, such work has failed to distinguish cases of the speaker flouting such a principle from cases where the speaker is either deceptive or holds a mistaken b...
cmp-lg/9806006
Dialogue Act Tagging with Transformation-Based Learning
cmp-lg cs.CL
For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a sparse data problem, we extract values of well-motivated features of utterances, such as speaker direction, punctuation marks, and a new feature, called dialogue act cues, whi...
cmp-lg/9806007
An Investigation of Transformation-Based Learning in Discourse
cmp-lg cs.CL
This paper presents results from the first attempt to apply Transformation-Based Learning to a discourse-level Natural Language Processing task. To address two limitations of the standard algorithm, we developed a Monte Carlo version of Transformation-Based Learning to make the method tractable for a wider range of p...
cmp-lg/9806008
Unlimited Vocabulary Grapheme to Phoneme Conversion for Korean TTS
cmp-lg cs.CL
This paper describes a grapheme-to-phoneme conversion method using phoneme connectivity and CCV conversion rules. The method consists of mainly four modules including morpheme normalization, phrase-break detection, morpheme to phoneme conversion and phoneme connectivity check. The morpheme normalization is to repla...
cmp-lg/9806009
Methods and Tools for Building the Catalan WordNet
cmp-lg cs.CL
In this paper we introduce the methodology used and the basic phases we followed to develop the Catalan WordNet, and shich lexical resources have been employed in its building. This methodology, as well as the tools we made use of, have been thought in a general way so that they could be applied to any other language...
cmp-lg/9806010
Towards a single proposal is spelling correction
cmp-lg cs.CL
The study presented here relies on the integrated use of different kinds of knowledge in order to improve first-guess accuracy in non-word context-sensitive correction for general unrestricted texts. State of the art spelling correction systems, e.g. ispell, apart from detecting spelling errors, also assist the user ...
cmp-lg/9806011
A Memory-Based Approach to Learning Shallow Natural Language Patterns
cmp-lg cs.CL
Recognizing shallow linguistic patterns, such as basic syntactic relationships between words, is a common task in applied natural language and text processing. The common practice for approaching this task is by tedious manual definition of possible pattern structures, often in the form of regular expressions or fini...
cmp-lg/9806012
Bayesian Stratified Sampling to Assess Corpus Utility
cmp-lg cs.CL
This paper describes a method for asking statistical questions about a large text corpus. We exemplify the method by addressing the question, "What percentage of Federal Register documents are real documents, of possible interest to a text researcher or analyst?" We estimate an answer to this question by evaluating 2...
cmp-lg/9806013
Can Subcategorisation Probabilities Help a Statistical Parser?
cmp-lg cs.CL
Research into the automatic acquisition of lexical information from corpora is starting to produce large-scale computational lexicons containing data on the relative frequencies of subcategorisation alternatives for individual verbal predicates. However, the empirical question of whether this type of frequency inform...
cmp-lg/9806014
Word Sense Disambiguation using Optimised Combinations of Knowledge Sources
cmp-lg cs.CL
Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowledge source. We describe a system which performs unrestricted word sense disambiguation (on all content words in free text) by combining different knowledge sources: semantic preferences, dictionary definitions and subje...
cmp-lg/9806015
Building Accurate Semantic Taxonomies from Monolingual MRDs
cmp-lg cs.CL
This paper presents a method that combines a set of unsupervised algorithms in order to accurately build large taxonomies from any machine-readable dictionary (MRD). Our aim is to profit from conventional MRDs, with no explicit semantic coding. We propose a system that 1) performs fully automatic exraction of taxonom...
cmp-lg/9806016
Using WordNet for Building WordNets
cmp-lg cs.CL
This paper summarises a set of methodologies and techniques for the fast construction of multilingual WordNets. The English WordNet is used in this approach as a backbone for Catalan and Spanish WordNets and as a lexical knowledge resource for several subtasks.
cmp-lg/9806017
Anchoring a Lexicalized Tree-Adjoining Grammar for Discourse
cmp-lg cs.CL
We here explore a ``fully'' lexicalized Tree-Adjoining Grammar for discourse that takes the basic elements of a (monologic) discourse to be not simply clauses, but larger structures that are anchored on variously realized discourse cues. This link with intra-sentential grammar suggests an account for different patter...
cmp-lg/9806018
Never Look Back: An Alternative to Centering
cmp-lg cs.CL
I propose a model for determining the hearer's attentional state which depends solely on a list of salient discourse entities (S-list). The ordering among the elements of the S-list covers also the function of the backward-looking center in the centering model. The ranking criteria for the S-list are based on the dis...
cmp-lg/9806019
An Empirical Investigation of Proposals in Collaborative Dialogues
cmp-lg cs.CL
We describe a corpus-based investigation of proposals in dialogue. First, we describe our DRI compliant coding scheme and report our inter-coder reliability results. Next, we test several hypotheses about what constitutes a well-formed proposal.
cmp-lg/9806020
Textual Economy through Close Coupling of Syntax and Semantics
cmp-lg cs.CL
We focus on the production of efficient descriptions of objects, actions and events. We define a type of efficiency, textual economy, that exploits the hearer's recognition of inferential links to material elsewhere within a sentence. Textual economy leads to efficient descriptions because the material that supports ...
cmp-lg/9807001
Evaluating a Focus-Based Approach to Anaphora Resolution
cmp-lg cs.CL
We present an approach to anaphora resolution based on a focusing algorithm, and implemented within an existing MUC (Message Understanding Conference) Information Extraction system, allowing quantitative evaluation against a substantial corpus of annotated real-world texts. Extensions to the basic focusing mechanism ...
cmp-lg/9807002
The Role of Verbs in Document Analysis
cmp-lg cs.CL
We present results of two methods for assessing the event profile of news articles as a function of verb type. The unique contribution of this research is the focus on the role of verbs, rather than nouns. Two algorithms are presented and evaluated, one of which is shown to accurately discriminate documents by type a...
cmp-lg/9807003
Centering in Dynamic Semantics
cmp-lg cs.CL
Centering theory posits a discourse center, a distinguished discourse entity that is the topic of a discourse. A simplified version of this theory is developed in a Dynamic Semantics framework. In the resulting system, the mechanism of center shift allows a simple, elegant analysis of a variety of phenomena involving...
cmp-lg/9807004
Word Clustering and Disambiguation Based on Co-occurrence Data
cmp-lg cs.CL
We address the problem of clustering words (or constructing a thesaurus) based on co-occurrence data, and using the acquired word classes to improve the accuracy of syntactic disambiguation. We view this problem as that of estimating a joint probability distribution specifying the joint probabilities of word pairs, s...
cmp-lg/9807005
Graph Interpolation Grammars as Context-Free Automata
cmp-lg cs.CL
A derivation step in a Graph Interpolation Grammar has the effect of scanning an input token. This feature, which aims at emulating the incrementality of the natural parser, restricts the formal power of GIGs. This contrasts with the fact that the derivation mechanism involves a context-sensitive device similar to tr...