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The Outilex software platform, which will be made available to research, development and industry, comprises software components implementing all the fundamental operations of written text processing: processing without lexicons, exploitation of lexicons and grammars, language resource management. All data are structured in XML formats, and also in more compact formats, either readable or binary, whenever necessary; the required format converters are included in the platform; the grammar formats allow for combining statistical approaches with resource-based approaches. Manually constructed lexicons for French and English, originating from the LADL, and of substantial coverage, will be distributed with the platform under LGPL-LR license.
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Outilex, plate-forme logicielle de traitement de textes écrits
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Speaking a language and achieving proficiency in another one is a highly complex process which requires the acquisition of various kinds of knowledge and skills, like the learning of words, rules and patterns and their connection to communicative goals (intentions), the usual starting point. To help the learner to acquire these skills we propose an enhanced, electronic version of an age old method: pattern drills (henceforth PDs). While being highly regarded in the fifties, PDs have become unpopular since then, partially because of their lack of grounding (natural context) and rigidity. Despite these shortcomings we do believe in the virtues of this approach, at least with regard to the acquisition of basic linguistic reflexes or skills (automatisms), necessary to survive in the new language. Of course, the method needs improvement, and we will show here how this can be achieved. Unlike tapes or books, computers are open media, allowing for dynamic changes, taking users' performances and preferences into account. Building an electronic version of PDs amounts to building an open resource, accomodatable to the users' ever changing needs.
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Let's get the student into the driver's seat
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This paper discusses two new procedures for extracting verb valences from raw texts, with an application to the Polish language. The first novel technique, the EM selection algorithm, performs unsupervised disambiguation of valence frame forests, obtained by applying a non-probabilistic deep grammar parser and some post-processing to the text. The second new idea concerns filtering of incorrect frames detected in the parsed text and is motivated by an observation that verbs which take similar arguments tend to have similar frames. This phenomenon is described in terms of newly introduced co-occurrence matrices. Using co-occurrence matrices, we split filtering into two steps. The list of valid arguments is first determined for each verb, whereas the pattern according to which the arguments are combined into frames is computed in the following stage. Our best extracted dictionary reaches an $F$-score of 45%, compared to an $F$-score of 39% for the standard frame-based BHT filtering.
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Valence extraction using EM selection and co-occurrence matrices
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Because of the wide variety of contemporary practices used in the automatic syntactic parsing of natural languages, it has become necessary to analyze and evaluate the strengths and weaknesses of different approaches. This research is all the more necessary because there are currently no genre- and domain-independent parsers that are able to analyze unrestricted text with 100% preciseness (I use this term to refer to the correctness of analyses assigned by a parser). All these factors create a need for methods and resources that can be used to evaluate and compare parsing systems. This research describes: (1) A theoretical analysis of current achievements in parsing and parser evaluation. (2) A framework (called FEPa) that can be used to carry out practical parser evaluations and comparisons. (3) A set of new evaluation resources: FiEval is a Finnish treebank under construction, and MGTS and RobSet are parser evaluation resources in English. (4) The results of experiments in which the developed evaluation framework and the two resources for English were used for evaluating a set of selected parsers.
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Framework and Resources for Natural Language Parser Evaluation
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A computational model of the construction of word meaning through exposure to texts is built in order to simulate the effects of co-occurrence values on word semantic similarities, paragraph by paragraph. Semantic similarity is here viewed as association. It turns out that the similarity between two words W1 and W2 strongly increases with a co-occurrence, decreases with the occurrence of W1 without W2 or W2 without W1, and slightly increases with high-order co-occurrences. Therefore, operationalizing similarity as a frequency of co-occurrence probably introduces a bias: first, there are cases in which there is similarity without co-occurrence and, second, the frequency of co-occurrence overestimates similarity.
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Effects of High-Order Co-occurrences on Word Semantic Similarities
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The derivation trees of a tree adjoining grammar provide a first insight into the sentence semantics, and are thus prime targets for generation systems. We define a formalism, feature-based regular tree grammars, and a translation from feature based tree adjoining grammars into this new formalism. The translation preserves the derivation structures of the original grammar, and accounts for feature unification.
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Feature Unification in TAG Derivation Trees
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Proof nets are a graph theoretical representation of proofs in various fragments of type-logical grammar. In spite of this basis in graph theory, there has been relatively little attention to the use of graph theoretic algorithms for type-logical proof search. In this paper we will look at several ways in which standard graph theoretic algorithms can be used to restrict the search space. In particular, we will provide an O(n4) algorithm for selecting an optimal axiom link at any stage in the proof search as well as a O(kn3) algorithm for selecting the k best proof candidates.
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Graph Algorithms for Improving Type-Logical Proof Search
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In this paper we describe the conception of a software toolkit designed for the construction, maintenance and collaborative use of a Generative Lexicon. In order to ease its portability and spreading use, this tool was built with free and open source products. We eventually tested the toolkit and showed it filters the adequate form of anaphoric reference to the modifier in endocentric compounds.
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A toolkit for a generative lexicon
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We describe a modular system for generating sentences from formal definitions of underlying linguistic structures using domain-specific languages. The system uses Java in general, Prolog for lexical entries and custom domain-specific languages based on Functional Grammar and Functional Discourse Grammar notation, implemented using the ANTLR parser generator. We show how linguistic and technological parts can be brought together in a natural language processing system and how domain-specific languages can be used as a tool for consistent formal notation in linguistic description.
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Computational Representation of Linguistic Structures using
Domain-Specific Languages
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The type-theoretic modelling of DRT that [degroote06] proposed features continuations for the management of the context in which a clause has to be interpreted. This approach, while keeping the standard definitions of quantifier scope, translates the rules of the accessibility constraints of discourse referents inside the semantic recipes. In this paper, we deal with additional rules for these accessibility constraints. In particular in the case of discourse referents introduced by proper nouns, that negation does not block, and in the case of rhetorical relations that structure discourses. We show how this continuation-based approach applies to those accessibility constraints and how we can consider the parallel management of various principles.
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Exploring a type-theoretic approach to accessibility constraint
modelling
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The goal of this paper is to present a model of children's semantic memory, which is based on a corpus reproducing the kinds of texts children are exposed to. After presenting the literature in the development of the semantic memory, a preliminary French corpus of 3.2 million words is described. Similarities in the resulting semantic space are compared to human data on four tests: association norms, vocabulary test, semantic judgments and memory tasks. A second corpus is described, which is composed of subcorpora corresponding to various ages. This stratified corpus is intended as a basis for developmental studies. Finally, two applications of these models of semantic memory are presented: the first one aims at tracing the development of semantic similarities paragraph by paragraph; the second one describes an implementation of a model of text comprehension derived from the Construction-integration model (Kintsch, 1988, 1998) and based on such models of semantic memory.
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A semantic space for modeling children's semantic memory
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In this paper we present two original methods for recognizing textual inference. First one is a modified resolution method such that some linguistic considerations are introduced in the unification of two atoms. The approach is possible due to the recent methods of transforming texts in logic formulas. Second one is based on semantic relations in text, as presented in WordNet. Some similarities between these two methods are remarked.
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Textual Entailment Recognizing by Theorem Proving Approach
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A large class of unsupervised algorithms for Word Sense Disambiguation (WSD) is that of dictionary-based methods. Various algorithms have as the root Lesk's algorithm, which exploits the sense definitions in the dictionary directly. Our approach uses the lexical base WordNet for a new algorithm originated in Lesk's, namely "chain algorithm for disambiguation of all words", CHAD. We show how translation from a language into another one and also text entailment verification could be accomplished by this disambiguation.
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A chain dictionary method for Word Sense Disambiguation and applications
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Measuring the similarity of short written contexts is a fundamental problem in Natural Language Processing. This article provides a unifying framework by which short context problems can be categorized both by their intended application and proposed solution. The goal is to show that various problems and methodologies that appear quite different on the surface are in fact very closely related. The axes by which these categorizations are made include the format of the contexts (headed versus headless), the way in which the contexts are to be measured (first-order versus second-order similarity), and the information used to represent the features in the contexts (micro versus macro views). The unifying thread that binds together many short context applications and methods is the fact that similarity decisions must be made between contexts that share few (if any) words in common.
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Computational Approaches to Measuring the Similarity of Short Contexts :
A Review of Applications and Methods
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The algorithm of the creation texts parallel corpora was presented. The algorithm is based on the use of "key words" in text documents, and on the means of their automated translation. Key words were singled out by means of using Russian and Ukrainian morphological dictionaries, as well as dictionaries of the translation of nouns for the Russian and Ukrainianlanguages. Besides, to calculate the weights of the terms in the documents, empiric-statistic rules were used. The algorithm under consideration was realized in the form of a program complex, integrated into the content-monitoring InfoStream system. As a result, a parallel bilingual corpora of web-publications containing about 30 thousand documents, was created
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About the creation of a parallel bilingual corpora of web-publications
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In this paper, we present an open-source parsing environment (Tuebingen Linguistic Parsing Architecture, TuLiPA) which uses Range Concatenation Grammar (RCG) as a pivot formalism, thus opening the way to the parsing of several mildly context-sensitive formalisms. This environment currently supports tree-based grammars (namely Tree-Adjoining Grammars, TAG) and Multi-Component Tree-Adjoining Grammars with Tree Tuples (TT-MCTAG)) and allows computation not only of syntactic structures, but also of the corresponding semantic representations. It is used for the development of a tree-based grammar for German.
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TuLiPA: Towards a Multi-Formalism Parsing Environment for Grammar
Engineering
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The ancient and extinct language Meroitic is investigated using Zipf's Law. In particular, since Meroitic is still undeciphered, the Zipf law analysis allows us to assess the quality of current texts and possible avenues for future investigation using statistical techniques.
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Investigation of the Zipf-plot of the extinct Meroitic language
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Julian Jaynes's profound humanitarian convictions not only prevented him from going to war, but would have prevented him from ever kicking a dog. Yet according to his theory, not only are language-less dogs unconscious, but so too were the speaking/hearing Greeks in the Bicameral Era, when they heard gods' voices telling them what to do rather than thinking for themselves. I argue that to be conscious is to be able to feel, and that all mammals (and probably lower vertebrates and invertebrates too) feel, hence are conscious. Julian Jaynes's brilliant analysis of our concepts of consciousness nevertheless keeps inspiring ever more inquiry and insights into the age-old mind/body problem and its relation to cognition and language.
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What It Feels Like To Hear Voices: Fond Memories of Julian Jaynes
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Meroitic is the still undeciphered language of the ancient civilization of Kush. Over the years, various techniques for decipherment such as finding a bilingual text or cognates from modern or other ancient languages in the Sudan and surrounding areas has not been successful. Using techniques borrowed from information theory and natural language statistics, similar words are paired and attempts are made to use currently defined words to extract at least partial meaning from unknown words.
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Constructing word similarities in Meroitic as an aid to decipherment
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Multilingual parallel texts (abbreviated to parallel texts) are linguistic versions of the same content ("translations"); e.g., the Maastricht Treaty in English and Spanish are parallel texts. This document is about creating an open architecture for the whole Authoring, Translation and Publishing Chain (ATP-chain) for the processing of parallel texts.
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Open architecture for multilingual parallel texts
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The paper deals with using descriptive mark-up to emphasize translation mistakes. The author postulates the necessity to develop a standard and formal XML-based way of describing translation mistakes. It is considered to be important for achieving impersonal translation quality assessment. Marked-up translations can be used in corpus translation studies; moreover, automatic translation assessment based on marked-up mistakes is possible. The paper concludes with setting up guidelines for further activity within the described field.
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Using descriptive mark-up to formalize translation quality assessment
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In the paper, we analyze the distribution of complexities in the Vai script, an indigenous syllabic writing system from Liberia. It is found that the uniformity hypothesis for complexities fails for this script. The models using Poisson distribution for the number of components and hyper-Poisson distribution for connections provide good fits in the case of the Vai script.
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Distribution of complexities in the Vai script
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In this article, some first elements of a computational modelling of the grammar of the Martiniquese French Creole dialect are presented. The sources of inspiration for the modelling is the functional description given by Damoiseau (1984), and Pinalie's & Bernabe's (1999) grammar manual. Based on earlier works in text generation (Vaillant, 1997), a unification grammar formalism, namely Tree Adjoining Grammars (TAG), and a modelling of lexical functional categories based on syntactic and semantic properties, are used to implement a grammar of Martiniquese Creole which is used in a prototype of text generation system. One of the main applications of the system could be its use as a tool software supporting the task of learning Creole as a second language. -- Nous pr\'esenterons dans cette communication les premiers travaux de mod\'elisation informatique d'une grammaire de la langue cr\'eole martiniquaise, en nous inspirant des descriptions fonctionnelles de Damoiseau (1984) ainsi que du manuel de Pinalie & Bernab\'e (1999). Prenant appui sur des travaux ant\'erieurs en g\'en\'eration de texte (Vaillant, 1997), nous utilisons un formalisme de grammaires d'unification, les grammaires d'adjonction d'arbres (TAG d'apr\`es l'acronyme anglais), ainsi qu'une mod\'elisation de cat\'egories lexicales fonctionnelles \`a base syntaxico-s\'emantique, pour mettre en oeuvre une grammaire du cr\'eole martiniquais utilisable dans une maquette de syst\`eme de g\'en\'eration automatique. L'un des int\'er\^ets principaux de ce syst\`eme pourrait \^etre son utilisation comme logiciel outil pour l'aide \`a l'apprentissage du cr\'eole en tant que langue seconde.
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Une grammaire formelle du créole martiniquais pour la génération
automatique
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This article describes the design of a common syntactic description for the core grammar of a group of related dialects. The common description does not rely on an abstract sub-linguistic structure like a metagrammar: it consists in a single FS-LTAG where the actual specific language is included as one of the attributes in the set of attribute types defined for the features. When the lang attribute is instantiated, the selected subset of the grammar is equivalent to the grammar of one dialect. When it is not, we have a model of a hybrid multidialectal linguistic system. This principle is used for a group of creole languages of the West-Atlantic area, namely the French-based Creoles of Haiti, Guadeloupe, Martinique and French Guiana.
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A Layered Grammar Model: Using Tree-Adjoining Grammars to Build a Common
Syntactic Kernel for Related Dialects
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We present the architecture of the UNL-French deconverter, which "generates" from the UNL interlingua by first"localizing" the UNL form for French, within UNL, and then applying slightly adapted but classical transfer and generation techniques, implemented in GETA's Ariane-G5 environment, supplemented by some UNL-specific tools. Online interaction can be used during deconversion to enhance output quality and is now used for development purposes. We show how interaction could be delayed and embedded in the postedition phase, which would then interact not directly with the output text, but indirectly with several components of the deconverter. Interacting online or offline can improve the quality not only of the utterance at hand, but also of the utterances processed later, as various preferences may be automatically changed to let the deconverter "learn".
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UNL-French deconversion as transfer & generation from an interlingua
with possible quality enhancement through offline human interaction
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Collocations are important for many tasks of Natural language processing such as information retrieval, machine translation, computational lexicography etc. So far many statistical methods have been used for collocation extraction. Almost all the methods form a classical crisp set of collocation. We propose a fuzzy logic approach of collocation extraction to form a fuzzy set of collocations in which each word combination has a certain grade of membership for being collocation. Fuzzy logic provides an easy way to express natural language into fuzzy logic rules. Two existing methods; Mutual information and t-test have been utilized for the input of the fuzzy inference system. The resulting membership function could be easily seen and demonstrated. To show the utility of the fuzzy logic some word pairs have been examined as an example. The working data has been based on a corpus of about one million words contained in different novels constituting project Gutenberg available on www.gutenberg.org. The proposed method has all the advantages of the two methods, while overcoming their drawbacks. Hence it provides a better result than the two methods.
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The Application of Fuzzy Logic to Collocation Extraction
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The Indus script is one of the major undeciphered scripts of the ancient world. The small size of the corpus, the absence of bilingual texts, and the lack of definite knowledge of the underlying language has frustrated efforts at decipherment since the discovery of the remains of the Indus civilisation. Recently, some researchers have questioned the premise that the Indus script encodes spoken language. Building on previous statistical approaches, we apply the tools of statistical language processing, specifically $n$-gram Markov chains, to analyse the Indus script for syntax. Our main results are that the script has well-defined signs which begin and end texts, that there is directionality and strong correlations in the sign order, and that there are groups of signs which appear to have identical syntactic function. All these require no {\it a priori} suppositions regarding the syntactic or semantic content of the signs, but follow directly from the statistical analysis. Using information theoretic measures, we find the information in the script to be intermediate between that of a completely random and a completely fixed ordering of signs. Our study reveals that the Indus script is a structured sign system showing features of a formal language, but, at present, cannot conclusively establish that it encodes {\it natural} language. Our $n$-gram Markov model is useful for predicting signs which are missing or illegible in a corpus of Indus texts. This work forms the basis for the development of a stochastic grammar which can be used to explore the syntax of the Indus script in greater detail.
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Statistical analysis of the Indus script using $n$-grams
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Cilibrasi and Vitanyi have demonstrated that it is possible to extract the meaning of words from the world-wide web. To achieve this, they rely on the number of webpages that are found through a Google search containing a given word and they associate the page count to the probability that the word appears on a webpage. Thus, conditional probabilities allow them to correlate one word with another word's meaning. Furthermore, they have developed a similarity distance function that gauges how closely related a pair of words is. We present a specific counterexample to the triangle inequality for this similarity distance function.
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Google distance between words
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A confidence measure is able to estimate the reliability of an hypothesis provided by a machine translation system. The problem of confidence measure can be seen as a process of testing : we want to decide whether the most probable sequence of words provided by the machine translation system is correct or not. In the following we describe several original word-level confidence measures for machine translation, based on mutual information, n-gram language model and lexical features language model. We evaluate how well they perform individually or together, and show that using a combination of confidence measures based on mutual information yields a classification error rate as low as 25.1% with an F-measure of 0.708.
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New Confidence Measures for Statistical Machine Translation
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In this paper we present the first step in a larger series of experiments for the induction of predicate/argument structures. The structures that we are inducing are very similar to the conceptual structures that are used in Frame Semantics (such as FrameNet). Those structures are called messages and they were previously used in the context of a multi-document summarization system of evolving events. The series of experiments that we are proposing are essentially composed from two stages. In the first stage we are trying to extract a representative vocabulary of words. This vocabulary is later used in the second stage, during which we apply to it various clustering approaches in order to identify the clusters of predicates and arguments--or frames and semantic roles, to use the jargon of Frame Semantics. This paper presents in detail and evaluates the first stage.
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What's in a Message?
| 1,329
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We report experiments about the syntactic variations of support verb constructions, a special type of multiword expressions (MWEs) containing predicative nouns. In these expressions, the noun can occur with or without the verb, with no clear-cut semantic difference. We extracted from a large French corpus a set of examples of the two situations and derived statistical results from these data. The extraction involved large-coverage language resources and finite-state techniques. The results show that, most frequently, predicative nouns occur without a support verb. This fact has consequences on methods of extracting or recognising MWEs.
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Syntactic variation of support verb constructions
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Formal work in linguistics has both produced and used important mathematical tools. Motivated by a survey of models for context and word meaning, syntactic categories, phrase structure rules and trees, an attempt is being made in the present paper to present a mathematical model for structuring of sentences from active voice to passive voice, which is is the form of a transitive verb whose grammatical subject serves as the patient, receiving the action of the verb. For this purpose we have parsed all sentences of a corpus and have generated Boolean groups for each of them. It has been observed that when we take constituents of the sentences as subgroups, the sequences of phrases form permutation roups. Application of isomorphism property yields permutation mapping between the important subgroups. It has resulted in a model for transformation of sentences from active voice to passive voice. A computer program has been written to enable the software developers to evolve grammar software for sentence transformations.
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Mathematical Model for Transformation of Sentences from Active Voice to
Passive Voice
| 1,331
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The paper presents a linguistic and computational model aiming at making the morphological structure of the lexicon emerge from the formal and semantic regularities of the words it contains. The model is word-based. The proposed morphological structure consists of (1) binary relations that connect each headword with words that are morphologically related, and especially with the members of its morphological family and its derivational series, and of (2) the analogies that hold between the words. The model has been tested on the lexicon of French using the TLFi machine readable dictionary.
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Acquisition of morphological families and derivational series from a
machine readable dictionary
| 1,332
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We examine the issue of digital formats for document encoding, archiving and publishing, through the specific example of "born-digital" scholarly journal articles. We will begin by looking at the traditional workflow of journal editing and publication, and how these practices have made the transition into the online domain. We will examine the range of different file formats in which electronic articles are currently stored and published. We will argue strongly that, despite the prevalence of binary and proprietary formats such as PDF and MS Word, XML is a far superior encoding choice for journal articles. Next, we look at the range of XML document structures (DTDs, Schemas) which are in common use for encoding journal articles, and consider some of their strengths and weaknesses. We will suggest that, despite the existence of specialized schemas intended specifically for journal articles (such as NLM), and more broadly-used publication-oriented schemas such as DocBook, there are strong arguments in favour of developing a subset or customization of the Text Encoding Initiative (TEI) schema for the purpose of journal-article encoding; TEI is already in use in a number of journal publication projects, and the scale and precision of the TEI tagset makes it particularly appropriate for encoding scholarly articles. We will outline the document structure of a TEI-encoded journal article, and look in detail at suggested markup patterns for specific features of journal articles.
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Encoding models for scholarly literature
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An important part of textual inference is making deductions involving monotonicity, that is, determining whether a given assertion entails restrictions or relaxations of that assertion. For instance, the statement 'We know the epidemic spread quickly' does not entail 'We know the epidemic spread quickly via fleas', but 'We doubt the epidemic spread quickly' entails 'We doubt the epidemic spread quickly via fleas'. Here, we present the first algorithm for the challenging lexical-semantics problem of learning linguistic constructions that, like 'doubt', are downward entailing (DE). Our algorithm is unsupervised, resource-lean, and effective, accurately recovering many DE operators that are missing from the hand-constructed lists that textual-inference systems currently use.
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Without a 'doubt'? Unsupervised discovery of downward-entailing
operators
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We describe a statistical model over linguistic areas and phylogeny. Our model recovers known areas and identifies a plausible hierarchy of areal features. The use of areas improves genetic reconstruction of languages both qualitatively and quantitatively according to a variety of metrics. We model linguistic areas by a Pitman-Yor process and linguistic phylogeny by Kingman's coalescent.
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Non-Parametric Bayesian Areal Linguistics
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A standard form of analysis for linguistic typology is the universal implication. These implications state facts about the range of extant languages, such as ``if objects come after verbs, then adjectives come after nouns.'' Such implications are typically discovered by painstaking hand analysis over a small sample of languages. We propose a computational model for assisting at this process. Our model is able to discover both well-known implications as well as some novel implications that deserve further study. Moreover, through a careful application of hierarchical analysis, we are able to cope with the well-known sampling problem: languages are not independent.
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A Bayesian Model for Discovering Typological Implications
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Current research in automatic single document summarization is dominated by two effective, yet naive approaches: summarization by sentence extraction, and headline generation via bag-of-words models. While successful in some tasks, neither of these models is able to adequately capture the large set of linguistic devices utilized by humans when they produce summaries. One possible explanation for the widespread use of these models is that good techniques have been developed to extract appropriate training data for them from existing document/abstract and document/headline corpora. We believe that future progress in automatic summarization will be driven both by the development of more sophisticated, linguistically informed models, as well as a more effective leveraging of document/abstract corpora. In order to open the doors to simultaneously achieving both of these goals, we have developed techniques for automatically producing word-to-word and phrase-to-phrase alignments between documents and their human-written abstracts. These alignments make explicit the correspondences that exist in such document/abstract pairs, and create a potentially rich data source from which complex summarization algorithms may learn. This paper describes experiments we have carried out to analyze the ability of humans to perform such alignments, and based on these analyses, we describe experiments for creating them automatically. Our model for the alignment task is based on an extension of the standard hidden Markov model, and learns to create alignments in a completely unsupervised fashion. We describe our model in detail and present experimental results that show that our model is able to learn to reliably identify word- and phrase-level alignments in a corpus of <document,abstract> pairs.
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Induction of Word and Phrase Alignments for Automatic Document
Summarization
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We present a document compression system that uses a hierarchical noisy-channel model of text production. Our compression system first automatically derives the syntactic structure of each sentence and the overall discourse structure of the text given as input. The system then uses a statistical hierarchical model of text production in order to drop non-important syntactic and discourse constituents so as to generate coherent, grammatical document compressions of arbitrary length. The system outperforms both a baseline and a sentence-based compression system that operates by simplifying sequentially all sentences in a text. Our results support the claim that discourse knowledge plays an important role in document summarization.
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A Noisy-Channel Model for Document Compression
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Entity detection and tracking (EDT) is the task of identifying textual mentions of real-world entities in documents, extending the named entity detection and coreference resolution task by considering mentions other than names (pronouns, definite descriptions, etc.). Like NE tagging and coreference resolution, most solutions to the EDT task separate out the mention detection aspect from the coreference aspect. By doing so, these solutions are limited to using only local features for learning. In contrast, by modeling both aspects of the EDT task simultaneously, we are able to learn using highly complex, non-local features. We develop a new joint EDT model and explore the utility of many features, demonstrating their effectiveness on this task.
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A Large-Scale Exploration of Effective Global Features for a Joint
Entity Detection and Tracking Model
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In this paper, we propose a pattern-based term extraction approach for Japanese, applying ACABIT system originally developed for French. The proposed approach evaluates termhood using morphological patterns of basic terms and term variants. After extracting term candidates, ACABIT system filters out non-terms from the candidates based on log-likelihood. This approach is suitable for Japanese term extraction because most of Japanese terms are compound nouns or simple phrasal patterns.
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Pattern Based Term Extraction Using ACABIT System
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We present a method of automatic translation (French/English) of Complex Lexical Units (CLU) for aiming at extracting a bilingual lexicon. Our modular system is based on linguistic properties (compositionality, polysemy, etc.). Different aspects of the multilingual Web are used to validate candidate translations and collect new terms. We first build a French corpus of Web pages to collect CLU. Three adapted processing stages are applied for each linguistic property : compositional and non polysemous translations, compositional polysemous translations and non compositional translations. Our evaluation on a sample of CLU shows that our technique based on the Web can reach a very high precision.
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Un système modulaire d'acquisition automatique de traductions à
partir du Web
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This paper presents the system called PATATRAS (PATent and Article Tracking, Retrieval and AnalysiS) realized for the IP track of CLEF 2009. Our approach presents three main characteristics: 1. The usage of multiple retrieval models (KL, Okapi) and term index definitions (lemma, phrase, concept) for the three languages considered in the present track (English, French, German) producing ten different sets of ranked results. 2. The merging of the different results based on multiple regression models using an additional validation set created from the patent collection. 3. The exploitation of patent metadata and of the citation structures for creating restricted initial working sets of patents and for producing a final re-ranking regression model. As we exploit specific metadata of the patent documents and the citation relations only at the creation of initial working sets and during the final post ranking step, our architecture remains generic and easy to extend.
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Multiple Retrieval Models and Regression Models for Prior Art Search
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OLAC was founded in 2000 for creating online databases of language resources. This paper intends to review the bottom-up distributed character of the project and proposes an extension of the architecture for Dravidian languages. An ontological structure is considered for effective natural language processing (NLP) and its advantages over statistical methods are reviewed
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An OLAC Extension for Dravidian Languages
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The paper reviews the hurdles while trying to implement the OLAC extension for Dravidian / Indian languages. The paper further explores the possibilities which could minimise or solve these problems. In this context, the Chinese system of text processing and the anusaaraka system are scrutinised.
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Empowering OLAC Extension using Anusaaraka and Effective text processing
using Double Byte coding
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Sandhi means to join two or more words to coin new word. Sandhi literally means `putting together' or combining (of sounds), It denotes all combinatory sound-changes effected (spontaneously) for ease of pronunciation. Sandhi-vicheda describes [5] the process by which one letter (whether single or cojoined) is broken to form two words. Part of the broken letter remains as the last letter of the first word and part of the letter forms the first letter of the next letter. Sandhi- Vicheda is an easy and interesting way that can give entirely new dimension that add new way to traditional approach to Hindi Teaching. In this paper using the Rule based algorithm we have reported an accuracy of 60-80% depending upon the number of rules to be implemented.
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Implementation of Rule Based Algorithm for Sandhi-Vicheda Of Compound
Hindi Words
| 1,345
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Following the principles of Cognitive Grammar, we concentrate on a model for reference resolution that attempts to overcome the difficulties previous approaches, based on the fundamental assumption that all reference (independent on the type of the referring expression) is accomplished via access to and restructuring of domains of reference rather than by direct linkage to the entities themselves. The model accounts for entities not explicitly mentioned but understood in a discourse, and enables exploitation of discursive and perceptual context to limit the set of potential referents for a given referring expression. As the most important feature, we note that a single mechanism is required to handle what are typically treated as diverse phenomena. Our approach, then, provides a fresh perspective on the relations between Cognitive Grammar and the problem of reference.
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Reference Resolution within the Framework of Cognitive Grammar
| 1,346
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We describe an encoding scheme for discourse structure and reference, based on the TEI Guidelines and the recommendations of the Corpus Encoding Specification (CES). A central feature of the scheme is a CES-based data architecture enabling the encoding of and access to multiple views of a marked-up document. We describe a tool architecture that supports the encoding scheme, and then show how we have used the encoding scheme and the tools to perform a discourse analytic task in support of a model of global discourse cohesion called Veins Theory (Cristea & Ide, 1998).
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Marking-up multiple views of a Text: Discourse and Reference
| 1,347
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It is widely recognized that the proliferation of annotation schemes runs counter to the need to re-use language resources, and that standards for linguistic annotation are becoming increasingly mandatory. To answer this need, we have developed a framework comprised of an abstract model for a variety of different annotation types (e.g., morpho-syntactic tagging, syntactic annotation, co-reference annotation, etc.), which can be instantiated in different ways depending on the annotator's approach and goals. In this paper we provide an overview of the framework, demonstrate its applicability to syntactic annotation, and show how it can contribute to comparative evaluation of parser output and diverse syntactic annotation schemes.
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A Common XML-based Framework for Syntactic Annotations
| 1,348
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This paper presents an abstract data model for linguistic annotations and its implementation using XML, RDF and related standards; and to outline the work of a newly formed committee of the International Standards Organization (ISO), ISO/TC 37/SC 4 Language Resource Management, which will use this work as its starting point. The primary motive for presenting the latter is to solicit the participation of members of the research community to contribute to the work of the committee.
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Standards for Language Resources
| 1,349
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Handwriting is an alternative method for entering texts composing Short Message Services. However, a whole new language features the texts which are produced. They include for instance abbreviations and other consonantal writing which sprung up for time saving and fashion. We have collected and processed a significant number of such handwriting SMS, and used various strategies to tackle this challenging area of handwriting recognition. We proposed to study more specifically three different phenomena: consonant skeleton, rebus, and phonetic writing. For each of them, we compare the rough results produced by a standard recognition system with those obtained when using a specific language model.
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Language Models for Handwritten Short Message Services
| 1,350
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Handwriting is an alternative method for entering texts which composed Short Message Services. However, a whole new language features the texts which are produced. They include for instance abbreviations and other consonantal writing which sprung up for time saving and fashion. We have collected and processed a significant number of such handwritten SMS, and used various strategies to tackle this challenging area of handwriting recognition. We proposed to study more specifically three different phenomena: consonant skeleton, rebus, and phonetic writing. For each of them, we compare the rough results produced by a standard recognition system with those obtained when using a specific language model to take care of them.
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Vers la reconnaissance de mini-messages manuscrits
| 1,351
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This article proposes a method to extract dependency structures from phrase-structure level parsing with Interaction Grammars. Interaction Grammars are a formalism which expresses interactions among words using a polarity system. Syntactical composition is led by the saturation of polarities. Interactions take place between constituents, but as grammars are lexicalized, these interactions can be translated at the level of words. Dependency relations are extracted from the parsing process: every dependency is the consequence of a polarity saturation. The dependency relations we obtain can be seen as a refinement of the usual dependency tree. Generally speaking, this work sheds new light on links between phrase structure and dependency parsing.
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Analyse en dépendances à l'aide des grammaires d'interaction
| 1,352
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We present a method for grouping the synonyms of a lemma according to its dictionary senses. The senses are defined by a large machine readable dictionary for French, the TLFi (Tr\'esor de la langue fran\c{c}aise informatis\'e) and the synonyms are given by 5 synonym dictionaries (also for French). To evaluate the proposed method, we manually constructed a gold standard where for each (word, definition) pair and given the set of synonyms defined for that word by the 5 synonym dictionaries, 4 lexicographers specified the set of synonyms they judge adequate. While inter-annotator agreement ranges on that task from 67% to at best 88% depending on the annotator pair and on the synonym dictionary being considered, the automatic procedure we propose scores a precision of 67% and a recall of 71%. The proposed method is compared with related work namely, word sense disambiguation, synonym lexicon acquisition and WordNet construction.
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Grouping Synonyms by Definitions
| 1,353
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There are many scientific problems generated by the multiple and conflicting alternative definitions of linguistic recursion and human recursive processing that exist in the literature. The purpose of this article is to make available to the linguistic community the standard mathematical definition of recursion and to apply it to discuss linguistic recursion. As a byproduct, we obtain an insight into certain "soft universals" of human languages, which are related to cognitive constructs necessary to implement mathematical reasoning, i.e. mathematical model theory.
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Mathematics, Recursion, and Universals in Human Languages
| 1,354
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Multimodal interfaces, combining the use of speech, graphics, gestures, and facial expressions in input and output, promise to provide new possibilities to deal with information in more effective and efficient ways, supporting for instance: - the understanding of possibly imprecise, partial or ambiguous multimodal input; - the generation of coordinated, cohesive, and coherent multimodal presentations; - the management of multimodal interaction (e.g., task completion, adapting the interface, error prevention) by representing and exploiting models of the user, the domain, the task, the interactive context, and the media (e.g. text, audio, video). The present document is intended to support the discussion on multimodal content representation, its possible objectives and basic constraints, and how the definition of a generic representation framework for multimodal content representation may be approached. It takes into account the results of the Dagstuhl workshop, in particular those of the informal working group on multimodal meaning representation that was active during the workshop (see http://www.dfki.de/~wahlster/Dagstuhl_Multi_Modality, Working Group 4).
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Towards Multimodal Content Representation
| 1,355
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Both syntax-phonology and syntax-semantics interfaces in Higher Order Grammar (HOG) are expressed as axiomatic theories in higher-order logic (HOL), i.e. a language is defined entirely in terms of provability in the single logical system. An important implication of this elegant architecture is that the meaning of a valid expression turns out to be represented not by a single, nor even by a few "discrete" terms (in case of ambiguity), but by a "continuous" set of logically equivalent terms. The note is devoted to precise formulation and proof of this observation.
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A Note On Higher Order Grammar
| 1,356
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Proofs, in Ludics, have an interpretation provided by their counter-proofs, that is the objects they interact with. We follow the same idea by proposing that sentence meanings are given by the counter-meanings they are opposed to in a dialectical interaction. The conception is at the intersection of a proof-theoretic and a game-theoretic accounts of semantics, but it enlarges them by allowing to deal with possibly infinite processes.
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Ludics and its Applications to natural Language Semantics
| 1,357
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Machine Translation in India is relatively young. The earliest efforts date from the late 80s and early 90s. The success of every system is judged from its evaluation experimental results. Number of machine translation systems has been started for development but to the best of author knowledge, no high quality system has been completed which can be used in real applications. Recently, Punjabi University, Patiala, India has developed Punjabi to Hindi Machine translation system with high accuracy of about 92%. Both the systems i.e. system under question and developed system are between same closely related languages. Thus, this paper presents the evaluation results of Hindi to Punjabi machine translation system. It makes sense to use same evaluation criteria as that of Punjabi to Hindi Punjabi Machine Translation System. After evaluation, the accuracy of the system is found to be about 95%.
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Evaluation of Hindi to Punjabi Machine Translation System
| 1,358
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Automated language processing is central to the drive to enable facilitated referencing of increasingly available Sanskrit E texts. The first step towards processing Sanskrit text involves the handling of Sanskrit compound words that are an integral part of Sanskrit texts. This firstly necessitates the processing of euphonic conjunctions or sandhis, which are points in words or between words, at which adjacent letters coalesce and transform. The ancient Sanskrit grammarian Panini's codification of the Sanskrit grammar is the accepted authority in the subject. His famed sutras or aphorisms, numbering approximately four thousand, tersely, precisely and comprehensively codify the rules of the grammar, including all the rules pertaining to sandhis. This work presents a fresh new approach to processing sandhis in terms of a computational schema. This new computational model is based on Panini's complex codification of the rules of grammar. The model has simple beginnings and is yet powerful, comprehensive and computationally lean.
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A New Computational Schema for Euphonic Conjunctions in Sanskrit
Processing
| 1,359
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Artificial Neural Network (ANN) s has widely been used for recognition of optically scanned character, which partially emulates human thinking in the domain of the Artificial Intelligence. But prior to recognition, it is necessary to segment the character from the text to sentences, words etc. Segmentation of words into individual letters has been one of the major problems in handwriting recognition. Despite several successful works all over the work, development of such tools in specific languages is still an ongoing process especially in the Indian context. This work explores the application of ANN as an aid to segmentation of handwritten characters in Assamese- an important language in the North Eastern part of India. The work explores the performance difference obtained in applying an ANN-based dynamic segmentation algorithm compared to projection- based static segmentation. The algorithm involves, first training of an ANN with individual handwritten characters recorded from different individuals. Handwritten sentences are separated out from text using a static segmentation method. From the segmented line, individual characters are separated out by first over segmenting the entire line. Each of the segments thus obtained, next, is fed to the trained ANN. The point of segmentation at which the ANN recognizes a segment or a combination of several segments to be similar to a handwritten character, a segmentation boundary for the character is assumed to exist and segmentation performed. The segmented character is next compared to the best available match and the segmentation boundary confirmed.
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ANN-based Innovative Segmentation Method for Handwritten text in
Assamese
| 1,360
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This paper presents a theoretical research based approach to ellipsis resolution in machine translation. The formula of discourse is applied in order to resolve ellipses. The validity of the discourse formula is analyzed by applying it to the real world text, i.e., newspaper fragments. The source text is converted into mono-sentential discourses where complex discourses require further dissection either directly into primitive discourses or first into compound discourses and later into primitive ones. The procedure of dissection needs further improvement, i.e., discovering as many primitive discourse forms as possible. An attempt has been made to investigate new primitive discourses or patterns from the given text.
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A Discourse-based Approach in Text-based Machine Translation
| 1,361
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This paper presents a mechanism of resolving unidentified lexical units in Text-based Machine Translation (TBMT). In a Machine Translation (MT) system it is unlikely to have a complete lexicon and hence there is intense need of a new mechanism to handle the problem of unidentified words. These unknown words could be abbreviations, names, acronyms and newly introduced terms. We have proposed an algorithm for the resolution of the unidentified words. This algorithm takes discourse unit (primitive discourse) as a unit of analysis and provides real time updates to the lexicon. We have manually applied the algorithm to news paper fragments. Along with anaphora and cataphora resolution, many unknown words especially names and abbreviations were updated to the lexicon.
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Resolution of Unidentified Words in Machine Translation
| 1,362
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The goal of this paper is two-fold: to present an abstract data model for linguistic annotations and its implementation using XML, RDF and related standards; and to outline the work of a newly formed committee of the International Standards Organization (ISO), ISO/TC 37/SC 4 Language Resource Management, which will use this work as its starting point.
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Standards for Language Resources
| 1,363
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A simple method for finding the entropy and redundancy of a reasonable long sample of English text by direct computer processing and from first principles according to Shannon theory is presented. As an example, results on the entropy of the English language have been obtained based on a total of 20.3 million characters of written English, considering symbols from one to five hundred characters in length. Besides a more realistic value of the entropy of English, a new perspective on some classic entropy-related concepts is presented. This method can also be extended to other Latin languages. Some implications for practical applications such as plagiarism-detection software, and the minimum number of words that should be used in social Internet network messaging, are discussed.
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A New Look at the Classical Entropy of Written English
| 1,364
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A natural language (or ordinary language) is a language that is spoken, written, or signed by humans for general-purpose communication, as distinguished from formal languages (such as computer-programming languages or the "languages" used in the study of formal logic). The computational activities required for enabling a computer to carry out information processing using natural language is called natural language processing. We have taken Assamese language to check the grammars of the input sentence. Our aim is to produce a technique to check the grammatical structures of the sentences in Assamese text. We have made grammar rules by analyzing the structures of Assamese sentences. Our parsing program finds the grammatical errors, if any, in the Assamese sentence. If there is no error, the program will generate the parse tree for the Assamese sentence
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Parsing of part-of-speech tagged Assamese Texts
| 1,365
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This paper presents a brief survey on Automatic Speech Recognition and discusses the major themes and advances made in the past 60 years of research, so as to provide a technological perspective and an appreciation of the fundamental progress that has been accomplished in this important area of speech communication. After years of research and development the accuracy of automatic speech recognition remains one of the important research challenges (e.g., variations of the context, speakers, and environment).The design of Speech Recognition system requires careful attentions to the following issues: Definition of various types of speech classes, speech representation, feature extraction techniques, speech classifiers, database and performance evaluation. The problems that are existing in ASR and the various techniques to solve these problems constructed by various research workers have been presented in a chronological order. Hence authors hope that this work shall be a contribution in the area of speech recognition. The objective of this review paper is to summarize and compare some of the well known methods used in various stages of speech recognition system and identify research topic and applications which are at the forefront of this exciting and challenging field.
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Speech Recognition by Machine, A Review
| 1,366
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Accurate systems for extracting Protein-Protein Interactions (PPIs) automatically from biomedical articles can help accelerate biomedical research. Biomedical Informatics researchers are collaborating to provide metaservices and advance the state-of-art in PPI extraction. One problem often neglected by current Natural Language Processing systems is the characteristic complexity of the sentences in biomedical literature. In this paper, we report on the impact that automatic simplification of sentences has on the performance of a state-of-art PPI extraction system, showing a substantial improvement in recall (8%) when the sentence simplification method is applied, without significant impact to precision.
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Sentence Simplification Aids Protein-Protein Interaction Extraction
| 1,367
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The complexity of sentences characteristic to biomedical articles poses a challenge to natural language parsers, which are typically trained on large-scale corpora of non-technical text. We propose a text simplification process, bioSimplify, that seeks to reduce the complexity of sentences in biomedical abstracts in order to improve the performance of syntactic parsers on the processed sentences. Syntactic parsing is typically one of the first steps in a text mining pipeline. Thus, any improvement in performance would have a ripple effect over all processing steps. We evaluated our method using a corpus of biomedical sentences annotated with syntactic links. Our empirical results show an improvement of 2.90% for the Charniak-McClosky parser and of 4.23% for the Link Grammar parser when processing simplified sentences rather than the original sentences in the corpus.
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Towards Effective Sentence Simplification for Automatic Processing of
Biomedical Text
| 1,368
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In this article, we record the main linguistic differences or singularities of 17th century English, analyse them morphologically and syntactically and propose equivalent forms in contemporary English. We show how 17th century texts may be transcribed into modern English, combining the use of electronic dictionaries with rules of transcription implemented as transducers. Apr\`es avoir expos\'e la constitution du corpus, nous recensons les principales diff\'erences ou particularit\'es linguistiques de la langue anglaise du XVIIe si\`ecle, les analysons du point de vue morphologique et syntaxique et proposons des \'equivalents en anglais contemporain (AC). Nous montrons comment nous pouvons effectuer une transcription automatique de textes anglais du XVIIe si\`ecle en anglais moderne, en combinant l'utilisation de dictionnaires \'electroniques avec des r\`egles de transcriptions impl\'ement\'ees sous forme de transducteurs.
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Étude et traitement automatique de l'anglais du XVIIe siècle :
outils morphosyntaxiques et dictionnaires
| 1,369
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If the use of the apostrophe in contemporary English often marks the Saxon genitive, it may also indicate the omission of one or more let-ters. Some writers (wrongly?) use it to mark the plural in symbols or abbreviations, visual-ised thanks to the isolation of the morpheme "s". This punctuation mark was imported from the Continent in the 16th century. During the 19th century its use was standardised. However the rules of its usage still seem problematic to many, including literate speakers of English. "All too often, the apostrophe is misplaced", or "errant apostrophes are springing up every-where" is a complaint that Internet users fre-quently come across when visiting grammar websites. Many of them detail its various uses and misuses, and attempt to correct the most common mistakes about it, especially its mis-use in the plural, called greengrocers' apostro-phes and humorously misspelled "greengro-cers apostrophe's". While studying English travel accounts published in the seventeenth century, we noticed that the different uses of this symbol may accompany various models of metaplasms. We were able to highlight the linguistic variations of some lexemes, and trace the origin of modern grammar rules gov-erning its usage.
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"Mind your p's and q's": or the peregrinations of an apostrophe in 17th
Century English
| 1,370
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The recognition of Arabic Named Entities (NE) is a problem in different domains of Natural Language Processing (NLP) like automatic translation. Indeed, NE translation allows the access to multilingual in-formation. This translation doesn't always lead to expected result especially when NE contains a person name. For this reason and in order to ameliorate translation, we can transliterate some part of NE. In this context, we propose a method that integrates translation and transliteration together. We used the linguis-tic NooJ platform that is based on local grammars and transducers. In this paper, we focus on sport domain. We will firstly suggest a refinement of the typological model presented at the MUC Conferences we will describe the integration of an Arabic transliteration module into translation system. Finally, we will detail our method and give the results of the evaluation.
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Recognition and translation Arabic-French of Named Entities: case of the
Sport places
| 1,371
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We are developing electronic dictionaries and transducers for the automatic processing of the Albanian Language. We will analyze the words inside a linear segment of text. We will also study the relationship between units of sense and units of form. The composition of words takes different forms in Albanian. We have found that morphemes are frequently concatenated or simply juxtaposed or contracted. The inflected grammar of NooJ allows constructing the dictionaries of flexed forms (declensions or conjugations). The diversity of word structures requires tools to identify words created by simple concatenation, or to treat contractions. The morphological tools of NooJ allow us to create grammatical tools to represent and treat these phenomena. But certain problems exceed the morphological analysis and must be represented by syntactical grammars.
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Morphological study of Albanian words, and processing with NooJ
| 1,372
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Maximum mutual information (MMI) is a model selection criterion used for hidden Markov model (HMM) parameter estimation that was developed more than twenty years ago as a discriminative alternative to the maximum likelihood criterion for HMM-based speech recognition. It has been shown in the speech recognition literature that parameter estimation using the current MMI paradigm, lattice-based MMI, consistently outperforms maximum likelihood estimation, but this is at the expense of undesirable convergence properties. In particular, recognition performance is sensitive to the number of times that the iterative MMI estimation algorithm, extended Baum-Welch, is performed. In fact, too many iterations of extended Baum-Welch will lead to degraded performance, despite the fact that the MMI criterion improves at each iteration. This phenomenon is at variance with the analogous behavior of maximum likelihood estimation -- at least for the HMMs used in speech recognition -- and it has previously been attributed to `over fitting'. In this paper, we present an analysis of lattice-based MMI that demonstrates, first of all, that the asymptotic behavior of lattice-based MMI is much worse than was previously understood, i.e. it does not appear to converge at all, and, second of all, that this is not due to `over fitting'. Instead, we demonstrate that the `over fitting' phenomenon is the result of standard methodology that exacerbates the poor behavior of two key approximations in the lattice-based MMI machinery. We also demonstrate that if we modify the standard methodology to improve the validity of these approximations, then the convergence properties of lattice-based MMI become benign without sacrificing improvements to recognition accuracy.
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Approximations to the MMI criterion and their effect on lattice-based
MMI
| 1,373
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Using Pustejovsky's "The Syntax of Event Structure" and Fong's "On Mending a Torn Dress" we give a glimpse of a Pustejovsky-like analysis to some example sentences in Fong. We attempt to give a framework for semantics to the noun phrases and adverbs as appropriate as well as the lexical entries for all words in the examples and critique both papers in light of our findings and difficulties.
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On Event Structure in the Torn Dress
| 1,374
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This document discusses an approach and its rudimentary realization towards automatic classification of PPs; the topic, that has not received as much attention in NLP as NPs and VPs. The approach is a rule-based heuristics outlined in several levels of our research. There are 7 semantic categories of PPs considered in this document that we are able to classify from an annotated corpus.
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Towards a Heuristic Categorization of Prepositional Phrases in English
with WordNet
| 1,375
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Rhetorical structure analysis (RSA) explores discourse relations among elementary discourse units (EDUs) in a text. It is very useful in many text processing tasks employing relationships among EDUs such as text understanding, summarization, and question-answering. Thai language with its distinctive linguistic characteristics requires a unique technique. This article proposes an approach for Thai rhetorical structure analysis. First, EDUs are segmented by two hidden Markov models derived from syntactic rules. A rhetorical structure tree is constructed from a clustering technique with its similarity measure derived from Thai semantic rules. Then, a decision tree whose features derived from the semantic rules is used to determine discourse relations.
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Thai Rhetorical Structure Analysis
| 1,376
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Combined with space-time coding, the orthogonal frequency division multiplexing (OFDM) system explores space diversity. It is a potential scheme to offer spectral efficiency and robust high data rate transmissions over frequency-selective fading channel. However, space-time coding impairs the system ability to suppress interferences as the signals transmitted from two transmit antennas are superposed and interfered at the receiver antennas. In this paper, we developed an adaptive beamforming based on least mean squared error algorithm and null deepening to combat co-channel interference (CCI) for the space-time coded OFDM (STC-OFDM) system. To illustrate the performance of the presented approach, it is compared to the null steering beamformer which requires a prior knowledge of directions of arrival (DOAs). The structure of space-time decoders are preserved although there is the use of beamformers before decoding. By incorporating the proposed beamformer as a CCI canceller in the STC-OFDM systems, the performance improvement is achieved as shown in the simulation results.
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Co-channel Interference Cancellation for Space-Time Coded OFDM Systems
Using Adaptive Beamforming and Null Deepening
| 1,377
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This article presents SLAM, an Automatic Solver for Lexical Metaphors like ?d\'eshabiller* une pomme? (to undress* an apple). SLAM calculates a conventional solution for these productions. To carry on it, SLAM has to intersect the paradigmatic axis of the metaphorical verb ?d\'eshabiller*?, where ?peler? (?to peel?) comes closer, with a syntagmatic axis that comes from a corpus where ?peler une pomme? (to peel an apple) is semantically and syntactically regular. We test this model on DicoSyn, which is a ?small world? network of synonyms, to compute the paradigmatic axis and on Frantext.20, a French corpus, to compute the syntagmatic axis. Further, we evaluate the model with a sample of an experimental corpus of the database of Flexsem
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SLAM : Solutions lexicales automatique pour métaphores
| 1,378
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Hidden Markov models (HMMs) have been successfully applied to automatic speech recognition for more than 35 years in spite of the fact that a key HMM assumption -- the statistical independence of frames -- is obviously violated by speech data. In fact, this data/model mismatch has inspired many attempts to modify or replace HMMs with alternative models that are better able to take into account the statistical dependence of frames. However it is fair to say that in 2010 the HMM is the consensus model of choice for speech recognition and that HMMs are at the heart of both commercially available products and contemporary research systems. In this paper we present a preliminary exploration aimed at understanding how speech data depart from HMMs and what effect this departure has on the accuracy of HMM-based speech recognition. Our analysis uses standard diagnostic tools from the field of statistics -- hypothesis testing, simulation and resampling -- which are rarely used in the field of speech recognition. Our main result, obtained by novel manipulations of real and resampled data, demonstrates that real data have statistical dependency and that this dependency is responsible for significant numbers of recognition errors. We also demonstrate, using simulation and resampling, that if we `remove' the statistical dependency from data, then the resulting recognition error rates become negligible. Taken together, these results suggest that a better understanding of the structure of the statistical dependency in speech data is a crucial first step towards improving HMM-based speech recognition.
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Why has (reasonably accurate) Automatic Speech Recognition been so hard
to achieve?
| 1,379
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The article provides lexical statistical analysis of K. Vonnegut's two novels and their Russian translations. It is found out that there happen some changes between the speed of word types and word tokens ratio change in the source and target texts. The author hypothesizes that these changes are typical for English-Russian translations, and moreover, they represent an example of Baker's translation feature of levelling out.
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Change of word types to word tokens ratio in the course of translation
(based on Russian translations of K. Vonnegut novels)
| 1,380
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Text documents are complex high dimensional objects. To effectively visualize such data it is important to reduce its dimensionality and visualize the low dimensional embedding as a 2-D or 3-D scatter plot. In this paper we explore dimensionality reduction methods that draw upon domain knowledge in order to achieve a better low dimensional embedding and visualization of documents. We consider the use of geometries specified manually by an expert, geometries derived automatically from corpus statistics, and geometries computed from linguistic resources.
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Linguistic Geometries for Unsupervised Dimensionality Reduction
| 1,381
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Developers express the meaning of the domain ideas in specifically selected identifiers and comments that form the target implemented code. Software maintenance requires knowledge and understanding of the encoded ideas. This paper presents a way how to create automatically domain vocabulary. Knowledge of domain vocabulary supports the comprehension of a specific domain for later code maintenance or evolution. We present experiments conducted in two selected domains: application servers and web frameworks. Knowledge of domain terms enables easy localization of chunks of code that belong to a certain term. We consider these chunks of code as "concepts" and their placement in the code as "concept location". Application developers may also benefit from the obtained domain terms. These terms are parts of speech that characterize a certain concept. Concepts are encoded in "classes" (OO paradigm) and the obtained vocabulary of terms supports the selection and the comprehension of the class' appropriate identifiers. We measured the following software products with our tool: JBoss, JOnAS, GlassFish, Tapestry, Google Web Toolkit and Echo2.
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Automatic derivation of domain terms and concept location based on the
analysis of the identifiers
| 1,382
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Poetry-writing in Sanskrit is riddled with problems for even those who know the language well. This is so because the rules that govern Sanskrit prosody are numerous and stringent. We propose a computational algorithm that converts prose given as E-text into poetry in accordance with the metrical rules of Sanskrit prosody, simultaneously taking care to ensure that sandhi or euphonic conjunction, which is compulsory in verse, is handled. The algorithm is considerably speeded up by a novel method of reducing the target search database. The algorithm further gives suggestions to the poet in case what he/she has given as the input prose is impossible to fit into any allowed metrical format. There is also an interactive component of the algorithm by which the algorithm interacts with the poet to resolve ambiguities. In addition, this unique work, which provides a solution to a problem that has never been addressed before, provides a simple yet effective speech recognition interface that would help the visually impaired dictate words in E-text, which is in turn versified by our Poetry Composer Engine.
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A Computational Algorithm based on Empirical Analysis, that Composes
Sanskrit Poetry
| 1,383
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The recognition and classification of Named Entities (NER) are regarded as an important component for many Natural Language Processing (NLP) applications. The classification is usually made by taking into account the immediate context in which the NE appears. In some cases, this immediate context does not allow getting the right classification. We show in this paper that the use of an extended syntactic context and large-scale resources could be very useful in the NER task.
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Les Entités Nommées : usage et degrés de précision et de
désambiguïsation
| 1,384
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In this chapter, we assume that systematically studying spatial markers semantics in language provides a means to reveal fundamental properties and concepts characterizing conceptual representations of space. We propose a formal system accounting for the properties highlighted by the linguistic analysis, and we use these tools for representing the semantic content of several spatial relations of French. The first part presents a semantic analysis of the expression of space in French aiming at describing the constraints that formal representations have to take into account. In the second part, after presenting the structure of our formal system, we set out its components. A commonsense geometry is sketched out and several functional and pragmatic spatial concepts are formalized. We take a special attention in showing that these concepts are well suited to representing the semantic content of several prepositions of French ('sur' (on), 'dans' (in), 'devant' (in front of), 'au-dessus' (above)), and in illustrating the inferential adequacy of these representations.
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La représentation formelle des concepts spatiaux dans la langue
| 1,385
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While previous linguistic and psycholinguistic research on space has mainly analyzed spatial relations, the studies reported in this paper focus on how language distinguishes among spatial entities. Descriptive and experimental studies first propose a classification of entities, which accounts for both static and dynamic space, has some cross-linguistic validity, and underlies adults' cognitive processing. Formal and computational analyses then introduce theoretical elements aiming at modelling these categories, while fulfilling various properties of formal ontologies (generality, parsimony, coherence...). This formal framework accounts, in particular, for functional dependences among entities underlying some part-whole descriptions. Finally, developmental research shows that language-specific properties have a clear impact on how children talk about space. The results suggest some cross-linguistic variability in children's spatial representations from an early age onwards, bringing into question models in which general cognitive capacities are the only determinants of spatial cognition during the course of development.
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Les entités spatiales dans la langue : étude descriptive, formelle
et expérimentale de la catégorisation
| 1,386
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Automatically detecting discourse segments is an important preliminary step towards full discourse parsing. Previous research on discourse segmentation have relied on the assumption that elementary discourse units (EDUs) in a document always form a linear sequence (i.e., they can never be nested). Unfortunately, this assumption turns out to be too strong, for some theories of discourse like SDRT allows for nested discourse units. In this paper, we present a simple approach to discourse segmentation that is able to produce nested EDUs. Our approach builds on standard multi-class classification techniques combined with a simple repairing heuristic that enforces global coherence. Our system was developed and evaluated on the first round of annotations provided by the French Annodis project (an ongoing effort to create a discourse bank for French). Cross-validated on only 47 documents (1,445 EDUs), our system achieves encouraging performance results with an F-score of 73% for finding EDUs.
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Learning Recursive Segments for Discourse Parsing
| 1,387
|
The Lambek calculus provides a foundation for categorial grammar in the form of a logic of concatenation. But natural language is characterized by dependencies which may also be discontinuous. In this paper we introduce the displacement calculus, a generalization of Lambek calculus, which preserves its good proof-theoretic properties while embracing discontinuiity and subsuming it. We illustrate linguistic applications and prove Cut-elimination, the subformula property, and decidability
|
Displacement Calculus
| 1,388
|
This paper describes in details the first version of Morphonette, a new French morphological resource and a new radically lexeme-based method of morphological analysis. This research is grounded in a paradigmatic conception of derivational morphology where the morphological structure is a structure of the entire lexicon and not one of the individual words it contains. The discovery of this structure relies on a measure of morphological similarity between words, on formal analogy and on the properties of two morphological paradigms:
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Morphonette: a morphological network of French
| 1,389
|
In the article, the project of quantitative parametrization of all texts by Ivan Franko is manifested. It can be made only by using modern computer techniques after the frequency dictionaries for all Franko's works are compiled. The paper describes the application spheres, methodology, stages, principles and peculiarities in the compilation of the frequency dictionary of the second half of the 19th century - the beginning of the 20th century. The relation between the Ivan Franko frequency dictionary, explanatory dictionary of writer's language and text corpus is discussed.
|
Quantitative parametrization of texts written by Ivan Franko: An attempt
of the project
| 1,390
|
Lexicon-Grammar tables constitute a large-coverage syntactic lexicon but they cannot be directly used in Natural Language Processing (NLP) applications because they sometimes rely on implicit information. In this paper, we introduce LGExtract, a generic tool for generating a syntactic lexicon for NLP from the Lexicon-Grammar tables. It is based on a global table that contains undefined information and on a unique extraction script including all operations to be performed for all tables. We also present an experiment that has been conducted to generate a new lexicon of French verbs and predicative nouns.
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A generic tool to generate a lexicon for NLP from Lexicon-Grammar tables
| 1,391
|
In the article, the methodology and the principles of the compilation of the Frequency dictionary for Ivan Franko's novel Dlja domashnjoho ohnyshcha (For the Hearth) are described. The following statistical parameters of the novel vocabulary are obtained: variety, exclusiveness, concentration indexes, correlation between word rank and text coverage, etc. The main quantitative characteristics of Franko's novels Perekhresni stezhky (The Cross-Paths) and Dlja domashnjoho ohnyshcha are compared on the basis of their frequency dictionaries.
|
Ivan Franko's novel Dlja domashnjoho ohnyshcha (For the Hearth) in the
light of the frequency dictionary
| 1,392
|
The ambition of a character recognition system is to transform a text document typed on paper into a digital format that can be manipulated by word processor software Unlike other languages, Arabic has unique features, while other language doesn't have, from this language these are seven or eight language such as ordo, jewie and Persian writing, Arabic has twenty eight letters, each of which can be linked in three different ways or separated depending on the case. The difficulty of the Arabic handwriting recognition is that, the accuracy of the character recognition which affects on the accuracy of the word recognition, in additional there is also two or three from for each character, the suggested solution by using artificial neural network can solve the problem and overcome the difficulty of Arabic handwriting recognition.
|
Offline Arabic Handwriting Recognition Using Artificial Neural Network
| 1,393
|
Indian languages have long history in World Natural languages. Panini was the first to define Grammar for Sanskrit language with about 4000 rules in fifth century. These rules contain uncertainty information. It is not possible to Computer processing of Sanskrit language with uncertain information. In this paper, fuzzy logic and fuzzy reasoning are proposed to deal to eliminate uncertain information for reasoning with Sanskrit grammar. The Sanskrit language processing is also discussed in this paper.
|
Fuzzy Modeling and Natural Language Processing for Panini's Sanskrit
Grammar
| 1,394
|
This companion paper complements the main DEFT'10 article describing the MARF approach (arXiv:0905.1235) to the DEFT'10 NLP challenge (described at http://www.groupes.polymtl.ca/taln2010/deft.php in French). This paper is aimed to present the complete result sets of all the conducted experiments and their settings in the resulting tables highlighting the approach and the best results, but also showing the worse and the worst and their subsequent analysis. This particular work focuses on application of the MARF's classical and NLP pipelines to identification tasks within various francophone corpora to identify decades when certain articles were published for the first track (Piste 1) and place of origin of a publication (Piste 2), such as the journal and location (France vs. Quebec). This is the sixth iteration of the release of the results.
|
Complete Complementary Results Report of the MARF's NLP Approach to the
DEFT 2010 Competition
| 1,395
|
The Right Frontier Constraint (RFC), as a constraint on the attachment of new constituents to an existing discourse structure, has important implications for the interpretation of anaphoric elements in discourse and for Machine Learning (ML) approaches to learning discourse structures. In this paper we provide strong empirical support for SDRT's version of RFC. The analysis of about 100 doubly annotated documents by five different naive annotators shows that SDRT's RFC is respected about 95% of the time. The qualitative analysis of presumed violations that we have performed shows that they are either click-errors or structural misconceptions.
|
Testing SDRT's Right Frontier
| 1,396
|
The Lambek-Grishin calculus is a symmetric extension of the Lambek calculus: in addition to the residuated family of product, left and right division operations of Lambek's original calculus, one also considers a family of coproduct, right and left difference operations, related to the former by an arrow-reversing duality. Communication between the two families is implemented in terms of linear distributivity principles. The aim of this paper is to complement the symmetry between (dual) residuated type-forming operations with an orthogonal opposition that contrasts residuated and Galois connected operations. Whereas the (dual) residuated operations are monotone, the Galois connected operations (and their duals) are antitone. We discuss the algebraic properties of the (dual) Galois connected operations, and generalize the (co)product distributivity principles to include the negative operations. We give a continuation-passing-style translation for the new type-forming operations, and discuss some linguistic applications.
|
Symmetric categorial grammar: residuation and Galois connections
| 1,397
|
We report on work in progress on extracting lexical simplifications (e.g., "collaborate" -> "work together"), focusing on utilizing edit histories in Simple English Wikipedia for this task. We consider two main approaches: (1) deriving simplification probabilities via an edit model that accounts for a mixture of different operations, and (2) using metadata to focus on edits that are more likely to be simplification operations. We find our methods to outperform a reasonable baseline and yield many high-quality lexical simplifications not included in an independently-created manually prepared list.
|
For the sake of simplicity: Unsupervised extraction of lexical
simplifications from Wikipedia
| 1,398
|
Researchers in textual entailment have begun to consider inferences involving 'downward-entailing operators', an interesting and important class of lexical items that change the way inferences are made. Recent work proposed a method for learning English downward-entailing operators that requires access to a high-quality collection of 'negative polarity items' (NPIs). However, English is one of the very few languages for which such a list exists. We propose the first approach that can be applied to the many languages for which there is no pre-existing high-precision database of NPIs. As a case study, we apply our method to Romanian and show that our method yields good results. Also, we perform a cross-linguistic analysis that suggests interesting connections to some findings in linguistic typology.
|
Don't 'have a clue'? Unsupervised co-learning of downward-entailing
operators
| 1,399
|
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