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We present a new approach to stochastic modeling of constraint-based grammars that is based on log-linear models and uses EM for estimation from unannotated data. The techniques are applied to an LFG grammar for German. Evaluation on an exact match task yields 86% precision for an ambiguity rate of 5.4, and 90% precisi... | Lexicalized Stochastic Modeling of Constraint-Based Grammars using
Log-Linear Measures and EM Training | 1,100 |
This paper presents the use of probabilistic class-based lexica for disambiguation in target-word selection. Our method employs minimal but precise contextual information for disambiguation. That is, only information provided by the target-verb, enriched by the condensed information of a probabilistic class-based lexic... | Using a Probabilistic Class-Based Lexicon for Lexical Ambiguity
Resolution | 1,101 |
In this thesis, we present two approaches to a rigorous mathematical and algorithmic foundation of quantitative and statistical inference in constraint-based natural language processing. The first approach, called quantitative constraint logic programming, is conceptualized in a clear logical framework, and presents a ... | Probabilistic Constraint Logic Programming. Formal Foundations of
Quantitative and Statistical Inference in Constraint-Based Natural Language
Processing | 1,102 |
We present some novel machine learning techniques for the identification of subcategorization information for verbs in Czech. We compare three different statistical techniques applied to this problem. We show how the learning algorithm can be used to discover previously unknown subcategorization frames from the Czech P... | Automatic Extraction of Subcategorization Frames for Czech | 1,103 |
We describe the CoNLL-2000 shared task: dividing text into syntactically related non-overlapping groups of words, so-called text chunking. We give background information on the data sets, present a general overview of the systems that have taken part in the shared task and briefly discuss their performance. | Introduction to the CoNLL-2000 Shared Task: Chunking | 1,104 |
Anaphora resolution is one of the major problems in natural language processing. It is also one of the important tasks in machine translation and man/machine dialogue. We solve the problem by using surface expressions and examples. Surface expressions are the words in sentences which provide clues for anaphora resoluti... | Anaphora Resolution in Japanese Sentences Using Surface Expressions and
Examples | 1,105 |
Coping with ambiguity has recently received a lot of attention in natural language processing. Most work focuses on the semantic representation of ambiguous expressions. In this paper we complement this work in two ways. First, we provide an entailment relation for a language with ambiguous expressions. Second, we give... | A Tableaux Calculus for Ambiguous Quantification | 1,106 |
Common wisdom has it that the bias of stochastic grammars in favor of shorter derivations of a sentence is harmful and should be redressed. We show that the common wisdom is wrong for stochastic grammars that use elementary trees instead of context-free rules, such as Stochastic Tree-Substitution Grammars used by Data-... | Parsing with the Shortest Derivation | 1,107 |
We present an LFG-DOP parser which uses fragments from LFG-annotated sentences to parse new sentences. Experiments with the Verbmobil and Homecentre corpora show that (1) Viterbi n best search performs about 100 times faster than Monte Carlo search while both achieve the same accuracy; (2) the DOP hypothesis which stat... | An improved parser for data-oriented lexical-functional analysis | 1,108 |
We describe a new framework for distilling information from word lattices to improve the accuracy of speech recognition and obtain a more perspicuous representation of a set of alternative hypotheses. In the standard MAP decoding approach the recognizer outputs the string of words corresponding to the path with the hig... | Finding consensus in speech recognition: word error minimization and
other applications of confusion networks | 1,109 |
Grammatical relationships (GRs) form an important level of natural language processing, but different sets of GRs are useful for different purposes. Therefore, one may often only have time to obtain a small training corpus with the desired GR annotations. To boost the performance from using such a small training corpus... | Using existing systems to supplement small amounts of annotated
grammatical relations training data | 1,110 |
The most effective paradigm for word sense disambiguation, supervised learning, seems to be stuck because of the knowledge acquisition bottleneck. In this paper we take an in-depth study of the performance of decision lists on two publicly available corpora and an additional corpus automatically acquired from the Web, ... | Exploring automatic word sense disambiguation with decision lists and
the Web | 1,111 |
This paper deals with the exploitation of dictionaries for the semi-automatic construction of lexicons and lexical knowledge bases. The final goal of our research is to enrich the Basque Lexical Database with semantic information such as senses, definitions, semantic relations, etc., extracted from a Basque monolingual... | Extraction of semantic relations from a Basque monolingual dictionary
using Constraint Grammar | 1,112 |
This paper explores the possibility to exploit text on the world wide web in order to enrich the concepts in existing ontologies. First, a method to retrieve documents from the WWW related to a concept is described. These document collections are used 1) to construct topic signatures (lists of topically related words) ... | Enriching very large ontologies using the WWW | 1,113 |
This paper revisits the one sense per collocation hypothesis using fine-grained sense distinctions and two different corpora. We show that the hypothesis is weaker for fine-grained sense distinctions (70% vs. 99% reported earlier on 2-way ambiguities). We also show that one sense per collocation does hold across corpor... | One Sense per Collocation and Genre/Topic Variations | 1,114 |
This article describes an algorithm for reducing the intermediate alphabets in cascades of finite-state transducers (FSTs). Although the method modifies the component FSTs, there is no change in the overall relation described by the whole cascade. No additional information or special algorithm, that could decelerate th... | Reduction of Intermediate Alphabets in Finite-State Transducer Cascades | 1,115 |
In this paper, we propose a method to extract descriptions of technical terms from Web pages in order to utilize the World Wide Web as an encyclopedia. We use linguistic patterns and HTML text structures to extract text fragments containing term descriptions. We also use a language model to discard extraneous descripti... | Utilizing the World Wide Web as an Encyclopedia: Extracting Term
Descriptions from Semi-Structured Texts | 1,116 |
In information retrieval research, precision and recall have long been used to evaluate IR systems. However, given that a number of retrieval systems resembling one another are already available to the public, it is valuable to retrieve novel relevant documents, i.e., documents that cannot be retrieved by those existin... | A Novelty-based Evaluation Method for Information Retrieval | 1,117 |
Cross-language information retrieval (CLIR), where queries and documents are in different languages, needs a translation of queries and/or documents, so as to standardize both of them into a common representation. For this purpose, the use of machine translation is an effective approach. However, computational cost is ... | Applying Machine Translation to Two-Stage Cross-Language Information
Retrieval | 1,118 |
This paper explores the usefulness of a technique from software engineering, code instrumentation, for the development of large-scale natural language grammars. Information about the usage of grammar rules in test and corpus sentences is used to improve grammar and testsuite, as well as adapting a grammar to a specific... | The Use of Instrumentation in Grammar Engineering | 1,119 |
Besides temporal information explicitly available in verbs and adjuncts, the temporal interpretation of a text also depends on general world knowledge and default assumptions. We will present a theory for describing the relation between, on the one hand, verbs, their tenses and adjuncts and, on the other, the eventuali... | Semantic interpretation of temporal information by abductive inference | 1,120 |
Texts in natural language contain a lot of temporal information, both explicit and implicit. Verbs and temporal adjuncts carry most of the explicit information, but for a full understanding general world knowledge and default assumptions have to be taken into account. We will present a theory for describing the relatio... | Abductive reasoning with temporal information | 1,121 |
We aim at finding the minimal set of fragments which achieves maximal parse accuracy in Data Oriented Parsing. Experiments with the Penn Wall Street Journal treebank show that counts of almost arbitrary fragments within parse trees are important, leading to improved parse accuracy over previous models tested on this tr... | Do All Fragments Count? | 1,122 |
This paper describes a novel approach to constructing phonotactic models. The underlying theoretical approach to phonological description is the multisyllable approach in which multiple syllable classes are defined that reflect phonotactically idiosyncratic syllable subcategories. A new finite-state formalism, OFS Mode... | Multi-Syllable Phonotactic Modelling | 1,123 |
Primitive Optimality Theory (OTP) (Eisner, 1997a; Albro, 1998), a computational model of Optimality Theory (Prince and Smolensky, 1993), employs a finite state machine to represent the set of active candidates at each stage of an Optimality Theoretic derivation, as well as weighted finite state machines to represent th... | Taking Primitive Optimality Theory Beyond the Finite State | 1,124 |
The data on 13 typologically different languages have been processed using a two-parameter word length model, based on 1-displaced uniform Poisson distribution. Statistical dependencies of the 2nd parameter on the 1st one are revealed for the German texts and genre of letters. | Mathematical Model of Word Length on the Basis of the Cebanov-Fucks
Distribution with Uniform Parameter Distribution | 1,125 |
A two-parameter model of word length measured by the number of syllables comprising it is proposed. The first parameter is dependent on language type, the second one - on text genre and reflects the degree of completion of synergetic processes of language optimization. | Two-parameter Model of Word Length "Language - Genre" | 1,126 |
George A. Miller said that human beings have only seven chunks in short-term memory, plus or minus two. We counted the number of bunsetsus (phrases) whose modifiees are undetermined in each step of an analysis of the dependency structure of Japanese sentences, and which therefore must be stored in short-term memory. Th... | Magical Number Seven Plus or Minus Two: Syntactic Structure Recognition
in Japanese and English Sentences | 1,127 |
The referential properties of noun phrases in the Japanese language, which has no articles, are useful for article generation in Japanese-English machine translation and for anaphora resolution in Japanese noun phrases. They are generally classified as generic noun phrases, definite noun phrases, and indefinite noun ph... | A Machine-Learning Approach to Estimating the Referential Properties of
Japanese Noun Phrases | 1,128 |
It is often useful to sort words into an order that reflects relations among their meanings as obtained by using a thesaurus. In this paper, we introduce a method of arranging words semantically by using several types of `{\sf is-a}' thesauri and a multi-dimensional thesaurus. We also describe three major applications ... | Meaning Sort - Three examples: dictionary construction, tagged corpus
construction, and information presentation system | 1,129 |
We have developed systems of two types for NTCIR2. One is an enhenced version of the system we developed for NTCIR1 and IREX. It submitted retrieval results for JJ and CC tasks. A variety of parameters were tried with the system. It used such characteristics of newspapers as locational information in the CC tasks. The ... | CRL at Ntcir2 | 1,130 |
This paper presents a corpus-based approach to word sense disambiguation where a decision tree assigns a sense to an ambiguous word based on the bigrams that occur nearby. This approach is evaluated using the sense-tagged corpora from the 1998 SENSEVAL word sense disambiguation exercise. It is more accurate than the av... | A Decision Tree of Bigrams is an Accurate Predictor of Word Sense | 1,131 |
The present paper shows meta-programming turn programming, which is rich enough to express arbitrary arithmetic computations. We demonstrate a type system that implements Peano arithmetics, slightly generalized to negative numbers. Certain types in this system denote numerals. Arithmetic operations on such types-numera... | Type Arithmetics: Computation based on the theory of types | 1,132 |
This paper presents a novel method of generating and applying hierarchical, dynamic topic-based language models. It proposes and evaluates new cluster generation, hierarchical smoothing and adaptive topic-probability estimation techniques. These combined models help capture long-distance lexical dependencies. Experimen... | Dynamic Nonlocal Language Modeling via Hierarchical Topic-Based
Adaptation | 1,133 |
The process of microplanning encompasses a range of problems in Natural Language Generation (NLG), such as referring expression generation, lexical choice, and aggregation, problems in which a generator must bridge underlying domain-specific representations and general linguistic representations. In this paper, we desc... | Microplanning with Communicative Intentions: The SPUD System | 1,134 |
We performed corpus correction on a modality corpus for machine translation by using such machine-learning methods as the maximum-entropy method. We thus constructed a high-quality modality corpus based on corpus correction. We compared several kinds of methods for corpus correction in our experiments and developed a g... | Correction of Errors in a Modality Corpus Used for Machine Translation
by Using Machine-learning Method | 1,135 |
A great deal of work has been done demonstrating the ability of machine learning algorithms to automatically extract linguistic knowledge from annotated corpora. Very little work has gone into quantifying the difference in ability at this task between a person and a machine. This paper is a first step in that direction... | Man [and Woman] vs. Machine: A Case Study in Base Noun Phrase Learning | 1,136 |
We describe a robust approach for linking already existing lexical/semantic hierarchies. We use a constraint satisfaction algorithm (relaxation labelling) to select --among a set of candidates-- the node in a target taxonomy that bests matches each node in a source taxonomy. In this paper we present the complete mappin... | A Complete WordNet1.5 to WordNet1.6 Mapping | 1,137 |
This paper compares two different ways of estimating statistical language models. Many statistical NLP tagging and parsing models are estimated by maximizing the (joint) likelihood of the fully-observed training data. However, since these applications only require the conditional probability distributions, these distri... | Joint and conditional estimation of tagging and parsing models | 1,138 |
This paper describes the functioning of a broad-coverage probabilistic top-down parser, and its application to the problem of language modeling for speech recognition. The paper first introduces key notions in language modeling and probabilistic parsing, and briefly reviews some previous approaches to using syntactic s... | Probabilistic top-down parsing and language modeling | 1,139 |
This thesis presents a broad-coverage probabilistic top-down parser, and its application to the problem of language modeling for speech recognition. The parser builds fully connected derivations incrementally, in a single pass from left-to-right across the string. We argue that the parsing approach that we have adopted... | Robust Probabilistic Predictive Syntactic Processing | 1,140 |
This paper describes a prototype system to visualize and animate 3D scenes from car accident reports, written in French. The problem of generating such a 3D simulation can be divided into two subtasks: the linguistic analysis and the virtual scene generation. As a means of communication between these two modules, we fi... | Generating a 3D Simulation of a Car Accident from a Written Description
in Natural Language: the CarSim System | 1,141 |
It is offered to consider word meanings changes in diachrony as semicontinuous random walk with reflecting and swallowing screens. The basic characteristics of word life cycle are defined. Verification of the model has been realized on the data of Russian words distribution on various age periods. | Historical Dynamics of Lexical System as Random Walk Process | 1,142 |
We present a probabilistic model that uses both prosodic and lexical cues for the automatic segmentation of speech into topically coherent units. We propose two methods for combining lexical and prosodic information using hidden Markov models and decision trees. Lexical information is obtained from a speech recognizer,... | Integrating Prosodic and Lexical Cues for Automatic Topic Segmentation | 1,143 |
We propose a method to generate large-scale encyclopedic knowledge, which is valuable for much NLP research, based on the Web. We first search the Web for pages containing a term in question. Then we use linguistic patterns and HTML structures to extract text fragments describing the term. Finally, we organize extracte... | Organizing Encyclopedic Knowledge based on the Web and its Application
to Question Answering | 1,144 |
Statistical NLP systems are frequently evaluated and compared on the basis of their performances on a single split of training and test data. Results obtained using a single split are, however, subject to sampling noise. In this paper we argue in favour of reporting a distribution of performance figures, obtained by re... | Using the Distribution of Performance for Studying Statistical NLP
Systems and Corpora | 1,145 |
We present a hybrid statistical and grammar-based system for surface natural language generation (NLG) that uses grammar rules, conditions on using those grammar rules, and corpus statistics to determine the word order. We also describe how this surface NLG module is implemented in a prototype conversational system, an... | Modeling informational novelty in a conversational system with a hybrid
statistical and grammar-based approach to natural language generation | 1,146 |
We explore many ways of using conceptual distance measures in Word Sense Disambiguation, starting with the Agirre-Rigau conceptual density measure. We use a generalized form of this measure, introducing many (parameterized) refinements and performing an exhaustive evaluation of all meaningful combinations. We finally o... | The Role of Conceptual Relations in Word Sense Disambiguation | 1,147 |
In this paper we analyze two question answering tasks : the TREC-8 question answering task and a set of reading comprehension exams. First, we show that Q/A systems perform better when there are multiple answer opportunities per question. Next, we analyze common approaches to two subproblems: term overlap for answer se... | Looking Under the Hood : Tools for Diagnosing your Question Answering
Engine | 1,148 |
This paper reports on the "Learning Computational Grammars" (LCG) project, a postdoc network devoted to studying the application of machine learning techniques to grammars suitable for computational use. We were interested in a more systematic survey to understand the relevance of many factors to the success of learnin... | Learning Computational Grammars | 1,149 |
Memory-based learning (MBL) has enjoyed considerable success in corpus-based natural language processing (NLP) tasks and is thus a reliable method of getting a high-level of performance when building corpus-based NLP systems. However there is a bottleneck in MBL whereby any novel testing item has to be compared against... | Combining a self-organising map with memory-based learning | 1,150 |
The task of creating indicative summaries that help a searcher decide whether to read a particular document is a difficult task. This paper examines the indicative summarization task from a generation perspective, by first analyzing its required content via published guidelines and corpus analysis. We show how these su... | Applying Natural Language Generation to Indicative Summarization | 1,151 |
Transformation-based learning has been successfully employed to solve many natural language processing problems. It achieves state-of-the-art performance on many natural language processing tasks and does not overtrain easily. However, it does have a serious drawback: the training time is often intorelably long, especi... | Transformation-Based Learning in the Fast Lane | 1,152 |
This paper presents a novel method that allows a machine learning algorithm following the transformation-based learning paradigm \cite{brill95:tagging} to be applied to multiple classification tasks by training jointly and simultaneously on all fields. The motivation for constructing such a system stems from the observ... | Multidimensional Transformation-Based Learning | 1,153 |
In the past several years, a number of different language modeling improvements over simple trigram models have been found, including caching, higher-order n-grams, skipping, interpolated Kneser-Ney smoothing, and clustering. We present explorations of variations on, or of the limits of, each of these techniques, inclu... | A Bit of Progress in Language Modeling | 1,154 |
Maximum entropy models are considered by many to be one of the most promising avenues of language modeling research. Unfortunately, long training times make maximum entropy research difficult. We present a novel speedup technique: we change the form of the model to use classes. Our speedup works by creating two maximum... | Classes for Fast Maximum Entropy Training | 1,155 |
The paper presents a study on the portability of statistical syntactic knowledge in the framework of the structured language model (SLM). We investigate the impact of porting SLM statistics from the Wall Street Journal (WSJ) to the Air Travel Information System (ATIS) domain. We compare this approach to applying the Mi... | Portability of Syntactic Structure for Language Modeling | 1,156 |
We argue in this paper that many common adverbial phrases generally taken to signal a discourse relation between syntactically connected units within discourse structure, instead work anaphorically to contribute relational meaning, with only indirect dependence on discourse structure. This allows a simpler discourse st... | Anaphora and Discourse Structure | 1,157 |
This paper describes a set of comparative experiments for the problem of automatically filtering unwanted electronic mail messages. Several variants of the AdaBoost algorithm with confidence-rated predictions [Schapire & Singer, 99] have been applied, which differ in the complexity of the base learners considered. Two ... | Boosting Trees for Anti-Spam Email Filtering | 1,158 |
Allowing users to interact through language borders is an interesting challenge for information technology. For the purpose of a computer assisted language learning system, we have chosen icons for representing meaning on the input interface, since icons do not depend on a particular language. However, a key limitation... | Modelling Semantic Association and Conceptual Inheritance for Semantic
Analysis | 1,159 |
Selectional preference learning methods have usually focused on word-to-class relations, e.g., a verb selects as its subject a given nominal class. This papers extends previous statistical models to class-to-class preferences, and presents a model that learns selectional preferences for classes of verbs. The motivation... | Learning class-to-class selectional preferences | 1,160 |
Two kinds of systems have been defined during the long history of WSD: principled systems that define which knowledge types are useful for WSD, and robust systems that use the information sources at hand, such as, dictionaries, light-weight ontologies or hand-tagged corpora. This paper tries to systematize the relation... | Knowledge Sources for Word Sense Disambiguation | 1,161 |
This paper explores the possibility of enriching the content of existing ontologies. The overall goal is to overcome the lack of topical links among concepts in WordNet. Each concept is to be associated to a topic signature, i.e., a set of related words with associated weights. The signatures can be automatically const... | Enriching WordNet concepts with topic signatures | 1,162 |
The mathematical distinction between prose and verse may be detected in writings that are not apparently lineated, for example in T. S. Eliot's "Burnt Norton", and Jim Crace's "Quarantine". In this paper we offer comments on appropriate statistical methods for such work, and also on the nature of formal innovation in t... | Testing for Mathematical Lineation in Jim Crace's "Quarantine" and T. S.
Eliot's "Four Quartets" | 1,163 |
The paper investigates the use of richer syntactic dependencies in the structured language model (SLM). We present two simple methods of enriching the dependencies in the syntactic parse trees used for intializing the SLM. We evaluate the impact of both methods on the perplexity (PPL) and word-error-rate(WER, N-best re... | Richer Syntactic Dependencies for Structured Language Modeling | 1,164 |
We present a method of constructing and using a cascade consisting of a left- and a right-sequential finite-state transducer (FST), T1 and T2, for part-of-speech (POS) disambiguation. Compared to an HMM, this FST cascade has the advantage of significantly higher processing speed, but at the cost of slightly lower accur... | Part-of-Speech Tagging with Two Sequential Transducers | 1,165 |
We aim at finding the minimal set of fragments which achieves maximal parse accuracy in Data Oriented Parsing. Experiments with the Penn Wall Street Journal treebank show that counts of almost arbitrary fragments within parse trees are important, leading to improved parse accuracy over previous models tested on this tr... | What is the minimal set of fragments that achieves maximal parse
accuracy? | 1,166 |
Structured language models for speech recognition have been shown to remedy the weaknesses of n-gram models. All current structured language models are, however, limited in that they do not take into account dependencies between non-headwords. We show that non-headword dependencies contribute to significantly improved ... | Combining semantic and syntactic structure for language modeling | 1,167 |
We describe an incremental unsupervised procedure to learn words from transcribed continuous speech. The algorithm is based on a conservative and traditional statistical model, and results of empirical tests show that it is competitive with other algorithms that have been proposed recently for this task. | A procedure for unsupervised lexicon learning | 1,168 |
A statistical model for segmentation and word discovery in continuous speech is presented. An incremental unsupervised learning algorithm to infer word boundaries based on this model is described. Results of empirical tests showing that the algorithm is competitive with other models that have been used for similar task... | A Statistical Model for Word Discovery in Transcribed Speech | 1,169 |
This paper describes experiments carried out using a variety of machine-learning methods, including the k-nearest neighborhood method that was used in a previous study, for the translation of tense, aspect, and modality. It was found that the support-vector machine method was the most precise of all the methods tested. | Using a Support-Vector Machine for Japanese-to-English Translation of
Tense, Aspect, and Modality | 1,170 |
The elastic-input neuro tagger and hybrid tagger, combined with a neural network and Brill's error-driven learning, have already been proposed for the purpose of constructing a practical tagger using as little training data as possible. When a small Thai corpus is used for training, these taggers have tagging accuracie... | Part of Speech Tagging in Thai Language Using Support Vector Machine | 1,171 |
This paper describes a universal model for paraphrasing that transforms according to defined criteria. We showed that by using different criteria we could construct different kinds of paraphrasing systems including one for answering questions, one for compressing sentences, one for polishing up, and one for transformin... | Universal Model for Paraphrasing -- Using Transformation Based on a
Defined Criteria -- | 1,172 |
This paper describes representations of time-dependent signals that are invariant under any invertible time-independent transformation of the signal time series. Such a representation is created by rescaling the signal in a non-linear dynamic manner that is determined by recently encountered signal levels. This techniq... | Blind Normalization of Speech From Different Channels and Speakers | 1,173 |
Treebank formats and associated software tools are proliferating rapidly, with little consideration for interoperability. We survey a wide variety of treebank structures and operations, and show how they can be mapped onto the annotation graph model, and leading to an integrated framework encompassing tree and non-tree... | An Integrated Framework for Treebanks and Multilayer Annotations | 1,174 |
Annotation graphs and annotation servers offer infrastructure to support the analysis of human language resources in the form of time-series data such as text, audio and video. This paper outlines areas of common need among empirical linguists and computational linguists. After reviewing examples of data and tools used... | Annotation Graphs and Servers and Multi-Modal Resources: Infrastructure
for Interdisciplinary Education, Research and Development | 1,175 |
Phonology, as it is practiced, is deeply computational. Phonological analysis is data-intensive and the resulting models are nothing other than specialized data structures and algorithms. In the past, phonological computation - managing data and developing analyses - was done manually with pencil and paper. Increasingl... | Computational Phonology | 1,176 |
Phonology is the systematic study of the sounds used in language, their internal structure, and their composition into syllables, words and phrases. Computational phonology is the application of formal and computational techniques to the representation and processing of phonological information. This chapter will prese... | Phonology | 1,177 |
Selectional preference learning methods have usually focused on word-to-class relations, e.g., a verb selects as its subject a given nominal class. This paper extends previous statistical models to class-to-class preferences, and presents a model that learns selectional preferences for classes of verbs, together with a... | Integrating selectional preferences in WordNet | 1,178 |
In this paper we describe the systems we developed for the English (lexical and all-words) and Basque tasks. They were all supervised systems based on Yarowsky's Decision Lists. We used Semcor for training in the English all-words task. We defined different feature sets for each language. For Basque, in order to extrac... | Decision Lists for English and Basque | 1,179 |
In this paper we describe the Senseval 2 Basque lexical-sample task. The task comprised 40 words (15 nouns, 15 verbs and 10 adjectives) selected from Euskal Hiztegia, the main Basque dictionary. Most examples were taken from the Egunkaria newspaper. The method used to hand-tag the examples produced low inter-tagger agr... | The Basque task: did systems perform in the upperbound? | 1,180 |
We present memory-based learning approaches to shallow parsing and apply these to five tasks: base noun phrase identification, arbitrary base phrase recognition, clause detection, noun phrase parsing and full parsing. We use feature selection techniques and system combination methods for improving the performance of th... | Memory-Based Shallow Parsing | 1,181 |
We present an algorithm that takes an unannotated corpus as its input, and returns a ranked list of probable morphologically related pairs as its output. The algorithm tries to discover morphologically related pairs by looking for pairs that are both orthographically and semantically similar, where orthographic similar... | Unsupervised discovery of morphologically related words based on
orthographic and semantic similarity | 1,182 |
Given the lack of word delimiters in written Japanese, word segmentation is generally considered a crucial first step in processing Japanese texts. Typical Japanese segmentation algorithms rely either on a lexicon and syntactic analysis or on pre-segmented data; but these are labor-intensive, and the lexico-syntactic t... | Mostly-Unsupervised Statistical Segmentation of Japanese Kanji Sequences | 1,183 |
This paper presents Ellogon, a multi-lingual, cross-platform, general-purpose text engineering environment. Ellogon was designed in order to aid both researchers in natural language processing, as well as companies that produce language engineering systems for the end-user. Ellogon provides a powerful TIPSTER-based inf... | Ellogon: A New Text Engineering Platform | 1,184 |
I propose a variable-free treatment of dynamic semantics. By "dynamic semantics" I mean analyses of donkey sentences ("Every farmer who owns a donkey beats it") and other binding and anaphora phenomena in natural language where meanings of constituents are updates to information states, for instance as proposed by Groe... | A variable-free dynamic semantics | 1,185 |
NLTK, the Natural Language Toolkit, is a suite of open source program modules, tutorials and problem sets, providing ready-to-use computational linguistics courseware. NLTK covers symbolic and statistical natural language processing, and is interfaced to annotated corpora. Students augment and replace existing componen... | NLTK: The Natural Language Toolkit | 1,186 |
We present two methods for unsupervised segmentation of words into morpheme-like units. The model utilized is especially suited for languages with a rich morphology, such as Finnish. The first method is based on the Minimum Description Length (MDL) principle and works online. In the second method, Maximum Likelihood (M... | Unsupervised Discovery of Morphemes | 1,187 |
An important component of any generation system is the mapping dictionary, a lexicon of elementary semantic expressions and corresponding natural language realizations. Typically, labor-intensive knowledge-based methods are used to construct the dictionary. We instead propose to acquire it automatically via a novel mul... | Bootstrapping Lexical Choice via Multiple-Sequence Alignment | 1,188 |
This paper presents an evaluation of an ensemble--based system that participated in the English and Spanish lexical sample tasks of Senseval-2. The system combines decision trees of unigrams, bigrams, and co--occurrences into a single classifier. The analysis is extended to include the Senseval-1 data. | Evaluating the Effectiveness of Ensembles of Decision Trees in
Disambiguating Senseval Lexical Samples | 1,189 |
This paper presents a comparative evaluation among the systems that participated in the Spanish and English lexical sample tasks of Senseval-2. The focus is on pairwise comparisons among systems to assess the degree to which they agree, and on measuring the difficulty of the test instances included in these tasks. | Assessing System Agreement and Instance Difficulty in the Lexical Sample
Tasks of Senseval-2 | 1,190 |
This paper describes the sixteen Duluth entries in the Senseval-2 comparative exercise among word sense disambiguation systems. There were eight pairs of Duluth systems entered in the Spanish and English lexical sample tasks. These are all based on standard machine learning algorithms that induce classifiers from sense... | Machine Learning with Lexical Features: The Duluth Approach to
Senseval-2 | 1,191 |
While recent retrieval techniques do not limit the number of index terms, out-of-vocabulary (OOV) words are crucial in speech recognition. Aiming at retrieving information with spoken queries, we fill the gap between speech recognition and text retrieval in terms of the vocabulary size. Given a spoken query, we generat... | A Method for Open-Vocabulary Speech-Driven Text Retrieval | 1,192 |
Cross-language information retrieval (CLIR), where queries and documents are in different languages, has of late become one of the major topics within the information retrieval community. This paper proposes a Japanese/English CLIR system, where we combine a query translation and retrieval modules. We currently target ... | Japanese/English Cross-Language Information Retrieval: Exploration of
Query Translation and Transliteration | 1,193 |
This paper proposes a method to analyze Japanese anaphora, in which zero pronouns (omitted obligatory cases) are used to refer to preceding entities (antecedents). Unlike the case of general coreference resolution, zero pronouns have to be detected prior to resolution because they are not expressed in discourse. Our me... | A Probabilistic Method for Analyzing Japanese Anaphora Integrating Zero
Pronoun Detection and Resolution | 1,194 |
This paper applies an existing query translation method to cross-language patent retrieval. In our method, multiple dictionaries are used to derive all possible translations for an input query, and collocational statistics are used to resolve translation ambiguity. We used Japanese/English parallel patent abstracts to ... | Applying a Hybrid Query Translation Method to Japanese/English
Cross-Language Patent Retrieval | 1,195 |
Given the growing number of patents filed in multiple countries, users are interested in retrieving patents across languages. We propose a multi-lingual patent retrieval system, which translates a user query into the target language, searches a multilingual database for patents relevant to the query, and improves the b... | PRIME: A System for Multi-lingual Patent Retrieval | 1,196 |
We report experimental results associated with speech-driven text retrieval, which facilitates retrieving information in multiple domains with spoken queries. Since users speak contents related to a target collection, we produce language models used for speech recognition based on the target collection, so as to improv... | Language Modeling for Multi-Domain Speech-Driven Text Retrieval | 1,197 |
Speech recognition has of late become a practical technology for real world applications. Aiming at speech-driven text retrieval, which facilitates retrieving information with spoken queries, we propose a method to integrate speech recognition and retrieval methods. Since users speak contents related to a target collec... | Speech-Driven Text Retrieval: Using Target IR Collections for
Statistical Language Model Adaptation in Speech Recognition | 1,198 |
This paper describes the results of some experiments exploring statistical methods to infer syntactic behavior of words and morphemes from a raw corpus in an unsupervised fashion. It shares certain points in common with Brown et al (1992) and work that has grown out of that: it employs statistical techniques to analyze... | Using eigenvectors of the bigram graph to infer morpheme identity | 1,199 |
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