waashk/dblp huggingface dataset:
applying and improving the restriction grammar approach for dutch patient discharge summaries. this paper starts by giving a short overview of one existing nlp project for the medical sublanguage (1). after having presented our objectives (2), we will describe the restriction grammar formalism (3), the datastructure we use for parsing (4) and our parser (5) enhanced with a special control structure (6). an attempt to build a bootstrap dictionary of medical terminology in a semi-automatic way will also be discussed (7). a brief evaluation (8) and a short outline of our future research (9) will conclude this article.
text genre detection using common word frequencies. in this paper we present a method for detecting the text genre quickly and easily following an approach originally proposed in authorship attribution studies which uses as style markers the frequencies of occurrence of the most frequent words in a training corpus (burrows, 1992). in contrast to this approach we use the frequencies of occurrence of the most frequent words of the entire written language. using as testing ground a part of the wall street journal corpus, we show that the most frequent words of the british national corpus, representing the most frequent words of the written english language, are more reliable discriminators of text genre in comparison to the most frequent words of the training corpus. moreover, the frequencies of occurrence of the most common punctuation marks play an important role in terms of accurate text categorization as well as when dealing with training data of limited size.
lexicase parsing: a lexicon-driven approach to syntactic analysis. this paper presents a lexicon-based approach to syntactic analysis, lexicase, and applies it to a lexicon-driven computational parsing system. the basic descriptive mechanism in a lexicase grammar is lexical features. the properties of lexical items are represented by contextual and non-contextual features, and generalizations are expressed as relationships among sets of these features and among sets of lexical entries. syntactic tree structures are representaed as notworks of pairwise dependency relationships among the words in a sentence. possible dependencies are marked as contextual features on individual lexical items, and lexicase parsing is a process of picking out words in a string and attaching dependents to them in accordance with their contextual features. lexicase is an appropriate vehicle for parsing because lexicase analyses are monostratal, flat, and relatively non-abstract, and it is well suited to machine translation because grammatical representations for corresponding sentences in two languages will be very similar to each other in structure and inter-constituent relations, and thus far easier to interconvert.
linguistic knowledge extraction from real language behavior. an approach to extract linguistic knowledge from real language behavior is described. this method depends on the extraction of word relations, patterns of which are obtained by structuring the dependency relations in sentences called kakari-uke relation in japanese. as the first step of this approach, an experiment of a word classification utilizing those patterns was made on the 4178 sentences of real language data. a system was made to analyze dependency structure of sentences utilizing the knowledge base obtained through this word classification and the effectiveness of the knowledge base was evaluated. to develop this approach further, the relation matrix which captures multiple interaction of words is proposed.
polibox: generating descriptions, comparisons, and recommendations from a database. we describe our ongoing work on "polibox", a web-based text generator producing adaptive hypertext from a product database, currently one of computational linguistics text-books. when given a specification of a desired ideal book, polibox selects suitable candidates from the database, and presents them one-by-one to the user. books are described, compared to one another, and, under the right circumstances, actively recommended. this project note concentrates on the stages of content selection, text planning and sentence planning.
talisman: un système multi-agents gouverné par des lois linguistiques pour le traitement de la langue naturelle. natural language processing raises the problem of ambiguities and multiple solutions which follow from them. the knowledge gained when using the morphosyntactic analyser crisstal showed how necessary it was to overcome this issue. the architecture with sequential levels, in which each module corresponds to a linguistic level (pretreatments, morphology, syntax, semantics) has shown its limits. a sequential architecture does not allow a real exchange between different modules. this leads to the non availability of the linguistic information for the reduction of ambiguities, at the moment they are needed.the necessity for cooperation between different modules has lead us to envisage a new architecture which stems from the techniques of distributed artificial intelligence.the paper presents this new architecture which based on distributed artificial intelligence techniques treats the inherent problems of natural language processing. one of the originalities resides in the distributed treatment of sentence analysis (as apposed to a classic sequential treatment) and in the introduction of linguistic laws which allow the management of the communication between agents, without appealing to a central control. the talisman system is an environment which integrates linguistic tools where different agents can bring into use different methods such as symbolic and/or statistic ones.the talisman system contributes to the following points in the linguistic domain:&bull;the restriction of ambiguities by agent cooperation,&bull;rendering structures less complex by using local grammar rules,&bull;the treatment of uncertain information.it can:&bull;function with partial analyses at different classical levels of analysis,&bull;change strategies according to the applications or the corpus used,&bull;use linguistic laws which are easily modifiable.at the implementation level, the system brings openess to the modification of dictionaries, grammars and strategies of analysis, and the necessary mechanisms for the integration of new modules.talisman is a linguistic environment based on the most recent techniques used in software engineering environments. it provides mechanisms for data and control integration of linguistic tools.this paper is organized as follows. after a short overview in section 2 about the problems of sequential architectures, we establish the main objectives of our work in section 3. we present, in section 4, the contribution of multi-agents systems "governed by laws". in section 5, we define the structure of an agent and of its society. the implementation is presented in section 6.
distributedness and non-linearity of lolita's semantic network. this paper describes semnet the internal knowledge representation for lolita. lolita is a large scale natural language engineering (nle) system. as such the internal representation must be richly expressive, natural (with respect to natural language), and efficient. in network representations knowledge is gleaned by traversing the graph. the paper introduces two properties, (distributedness and non-linearity) of networks which directly relate to the efficiency by which knowledge is obtained. semnet is shown to have the specified properties thus distinguishing it (in terms of efficiency) as a suitable representation for large scale nle.
a distributed architecture for text analysis in french: an application to complex linguistic phenomena processing. most natural language processing systems use a sequential architecture embodying classical linguistic layers. when one works with a general language and not a sublanguage, there are different cases of ambiguities at different classical levels; and more particularly when one works on complex language phenomena analysis (coordination, ellipsis, negation...) it is difficult to take into account all the different types of these constructions with a general grammar. indeed, the inconvenience of this approach is the possible risk of a combinatory explosion. so we have defined the talisman architecture that includes linguistic agents that correspond either to classical levels in linguistics (morphology, syntax, semantic) or to complex language phenomena analysis.
morphological aspect of japanese language processing. a comprehensive grammatical model produced for analyzing the agglutinated structure which characterizes the japanese language is presented. this model, which includes extensively idiomatic postpositional expressions as terminals, is quite effective for the development of the japanese language processor receptive to a reasonable variety of sentential forms and applicable to relatively wide fields.
parsing german. the first part of this paper is dedicated to an overview of the parser of the system vie-lang (viennese language understanding system). the parser is a production system which uses an interleaved method that combines syntax and semantics. it parses directly into the internal representation of the system, without producing an intermediate syntactic structure. the last part discusses the relationship between some special features of the german language, and properties of the parser that originate in the language.
content characterization using word shape tokens. by quickly classifying character images into character shape categories, it is possible to automatically extract syntactic information from the text of document images without optical character recognition. using word shape tokens composed of these character shape codes, a properly trained text tagger can extract part-of-speech information from scanned document images. later components of a document processing system can then use this information to locate topics, characterize document style, and assist in information retrieval.
treating 'free word order' in machine translation. in free word order languages, every sentence is embedded in its specific context. the order of constituents is determined by the categories theme, rheme and contraslive focus. this paper shows how to recognise and to translate these categories automatically on a sentential basis, so that sentence embedding can be achieved without having to refer to the context. traditionally neglected modifier classes are fully covered by the proposed method.
directing the generation of living space description. we have developed a computational model of the process of describing the layout of an apartment or house, a much-studied discourse task first characterized linguistically by linde (1974). the model is embodied in a program, apt, that can reproduce segments of actual tape-recorded descriptions, using organizational and discourse strategies derived through analysis of our corpus.
a dynamic language model based on individual word domains. we present a new statistical language model based on a combination of individual word language models. each word model is built from an individual corpus which is formed by extracting those subsets of the entire training corpus which contain that significant word. we also present a novel way of combining language models called the "union model", based on a logical union of intersections, and use this to combine the language models obtained for the significant words from a cache. the initial results with the new model provide a 20% reduction in language model perplexity over the standard 3-gram approach.
on the semantics of focus phenomena in eurotra. in this paper, we discuss issues connected to the phenomenon of linguistic focus or information distribution in the sentence in the context of the multi-lingual machine translation project eurotra. we shall present some of the arguments why a consideration of focus phenomena is important for the determination of linear order and for semantic interpretation. we shall proceed, in sections 2 and 3 of the paper, to mention the main lines of development in the dicussion of focus phenomena in computational linguistics and in linguistics respectively. section 4 contains an illustration of a pilot implementation covering some aspects of focus phenomena in eurotra-d.
extracting semantic clusters from the alignment of definitions. through the alignment of definitions from two or more different sources, it is possible to retrieve pairs of words that can be used indistinguishably in the same sentence without changing the meaning of the concept. as lexicographic work exploits common defining schemes, such as genus and differentia, a concept is similarly defined by different dictionaries. the difference in words used between two lexicographic sources lets us extend the lexical knowledge base, so that clustering is available through merging two or more dictionaries into a single database and then using an appropriate alignment technique. since alignment starts from the same entry of two dictionaries, clustering is faster than any other technique.the algorithm introduced here is analogy-based, and starts from calculating the levenshtein distance, which is a variation of the edit distance, and allows us to align the definitions. as a measure of similarity, the concept of longest collocation couple is introduced, which is the basis of clustering similar words. the process iterates, replacing similar pairs of words in the definitions until no new clusters are found.
augmenting noun taxonomies by combining lexical similarity metrics. this paper presents a method for augmenting taxonomies with domain information using a simple combination of three existing lexical similarity metrics. the combined approach is evaluated by comparing their results against the annotated semcor corpus. an implementation is described in which wordnet is augmented with thesaural information from the cide+ machine readable dictionary.
computer simulation of spontaneous speech production. this paper pinpoints some of the problems faced when a computer text production model (commentator) is to produce spontaneous speech, in particular the problem of chunking the utterances in order to get natural prosodic units. the paper proposes a buffer model which allows the accumulation and delay of phonetic material until a chunk of the desired size has been built up. several phonetic studies have suggested a similar temporary storage in order to explain intonation slopes, rythmical patterns, speech errors and speech disorders. small-scale simulations of the whole verbalization process from perception and thought to sounds, hesitation behaviour, pausing, speech errors, sound changes and speech disorders are presented.
automatic lexical acquisition based on statistical distributions. we automatically classify verbs into lexical semantic classes, based on distributions of indicators of verb alternations, extracted from a very large annotated corpus. we address a problem which is particularly difficult because the verb classes, although semantically different, show similar surface syntactic behavior. five grammatical features are sufficient to reduce error rate by more than 50% over chance: we achieve almost 70% accuracy in a task whose baseline performance is 34%, and whose expert-based upper bound we calculated at 86.5%. we conclude that corpus-driven extraction of grammatical features is a promising methodology for find-grained verb classification.
island parsing and bidirectional charts. chart parsing is directional in the sense that it works from the starting point (usually the beginning of the sentence) extending its activity usually in a rightward manner. we shall introduce the concept of a chart that works outward from islands and makes sense of as much of the sentence as it is actually possible, and after that will lead to predictions of missing fragments. so, for any place where the easily identifiable fragments occur in the sentence, the process will extend to both the left and the right of the islands, until possibly completely missing fragments are reached. at that point, by virtue of the fact that both a left and a right context were found, heuristics can be introduced that predict the nature of the missing fragments.
unifying disjunctive feature structures. this paper describes an algorithm for unifying disjunctive feature structures. unlike previous algorithms, except eisele & d&ouml;rre (1990), this algorithm is as fast as an algorithm without disjunction when disjunctions do not participate in the unification, it is also as fast as an algorithm handling only local disjunctions when there are only local disjunctions, and expensive only in the case of unifying full disjunction. the description is given in the framework of graph unification algorithms which makes it easy to implement as an extension of such an algorithm.
intex: a corpus processing system. intex is a text processor; it is usually used to parse corpora of several megabytes. it includes several built-in large coverage dictionaries and grammars represented by graphs; the user may add his/her own dictionaries and grammars. these tools are applied to texts in order to locate lexical and syntactic patterns, remove ambiguities, and tag words. intex builds concordances and indexes of all types of patterns; it is used by linguists to analyse corpora, but can also be viewed as an information retrieval system.
achieving flexibility in unification formalisms. we argue that flexibility is an important property for unification-based formalisms. by flexibility we mean the ability for the user to modify and extend the formalism according to the needs of his problem. the paper discusses some properties necessary to achieve a flexible formalism and presents the fluf formalism as a realization of these ideas.
computational complexity of probabilistic disambiguation by means of tree-grammars. this paper studies the computational complexity of disambiguation under probabilistic tree-grammars as in (bod, 1992; schabes and waters, 1993). it presents a proof that the following problems are np-hard: computing the most probable parse from a sentence or from a word-graph, and computing the most probable sentence (mps) from a word-graph. the np-hardness of computing the mps from a word-graph also holds for stochastic context-free grammars (scfgs).
an approach to non-singular terms in discourse. a new theory of names and descriptions that offers a uniform treatment for many types of non-singular concepts found in natural language discourse is presented. we introduce a layered model of the language denotational base (the universe) in which every world object is assigned a layer (level) reflecting its relative singularity with respect in other objects in the universe. we define the notion of relative singularity of world objects as an abstraction class of the layermembership relation
the costs of inheritance in semantic networks. questioning texts represented in semantic relations1 requires the recognition that synonyms, instances, and hyponyms may all satisfy a questioned term. a basic procedure for accomplishing such loose matching using inheritance from a taxonomic organization of the dictionary is defined in analogy with the unification algorithm used for theorem proving, and the costs of its application are analyzed. it is concluded that inheritance logic can profitably be included in the basic questioning procedure.
how to invert a natural language parser into an efficient generator: an algorithm for logic grammars. the use of a single grammar in natural language parsing and generation is most desirable for variety of reasons including efficiency, perspicuity, integrity, robustness, and a certain amount of elegance. in this paper we present an algorithm for automated inversion of a prolog-coded unification parser into an efficient unification generator, using the collections of minimal sets of essential arguments (msea) for predicates. the algorithm is also applicable to more abstract systems for writing logic grammars, such as dcg.
ttp: a fast and robust parser for natural language. in this paper we describe ttp, a fast and robust natural language parser which can analyze written text and generate regularized parse structures for sentences and phrases at the speed of approximately 0.5 sec/sentence, or 44 word per second. the parser is based on a wide coverage grammar for english, developed by the new york university's linguistic string project, and it uses the machine-readable version of the oxford advanced learner's dictionary as a source of its basic vocabulary. the parser operates on stochastically tagged text, and contains a powerful skip-and-fit recovery mechanism that allows it to deal with extra-grammatical input and to operate effectively under a severe time pressure. empirical experiments, testing parser's speed and accuracy, were performed on several collections: a collection of technical abstracts (cacm-3204), a corpus of news messages (muc-3), a selection from acm computer library database, and a collection of wall street journal articles, approximately 50 million words in total.
how to deal with ambiguities while parsing: exam - a semantic processing system for japanese language. it is difficult for a natural language understanding system (nlus) to deal with ambiguities. there is a dilemma: an nlus must be able to produce plausible interpretations for given sentences, avoiding the combinatorial explosion of possible interpretations. furthermore, it is desirable for an nlus to produce several interpretations if they are equally plausible. exam, the system described in this paper, is an experimental text understanding system designed to deal with ambiguities effectively and efficiently.
syntactic constraints on relativization in japanese. this paper discusses the formalization of relative clauses in japanese based on jpsg framework. we characterize them as adjuncts to nouns, and formalize them in terms of constraints among grammatical features. furthermore, we claim that there is a constraint on the number of slash elements and show the supporting facts.
a self-learning universal concept spotter. we describe the universal spotter, a system for identifying in-text references to entities of an arbitrary, user-specified type, such as people, organizations, equipment, products, materials, etc. starting with some initial seed examples, and a training text corpus, the system generates rules that will find further concepts of the same type. the initial seed information is provided by the user in the form of a typical lexical context in which the entities to be spotted occur, e.g., "the name ends with co.", or "to the right of produced or made", and so forth, or by simply supplying examples of the concept itself, e.g., ford taurus, gas turbine, big mac. in addition, negative examples can be supplied, if known. given a sufficiently large training corpus, an unsupervised learning process is initiated in which the system will: (1) find instances of the sought-after concept using the seed-context information while maximizing recall and precision; (2) find additional contexts in which these entities occur; and (3) expand the initial seed-context with selected new contexts to find even more entities. preliminary results of creating spotters for organizations and products are discussed.
anaphor resolution and the scope of syntactic constraints. an anaphor resolution algorithm is presented which relies on a combination of strategies for narrowing down and selecting from antecedent sets for reflexive pronouns, nonreflexive pronouns, and common nouns. the work focuses on syntactic restrictions which are derived from chomsky's binding theory. it is discussed how these constraints can be incorporated adequately in an anaphor resolution algorithm. moreover, by showing that pragmatic inferences may be necessary, the limits of syntactic restrictions are elucidated.