waashk/dblp huggingface dataset:
automatic glossary extraction: beyond terminology identification. this paper describes a method for automatically extracting domain-specific glossaries from large document collections. we show that, compared with current text analysis methods for extracting technical terminology from text, our extracted glossaries more successfully support applications requiring knowledge of domain concepts. after presenting our methods, we illustrate the output of glossex, our glossary extraction tool, and present an informal evaluation of its performance.
informed parsing for coordination with combinatory categorial grammar. coordination in natural language hampers efficient parsing, especially due to the multiple and mostly unintended candidate conjuncts/disjuncts in a given sentence that shows structural ambiguity. the problem gets more serious in a combinatory categorial grammar framework, which is well known for its competent treatment of coordination, as the flexibility of syntactic analysis often strikes back as spurious ambiguity. we propose to address these ambiguities with predicate argument structures and semantic co-occurrence similarity information, and present encouraging results.
language acquisition as learning. chomsky's proposition that language is handled by a language-specific faculty needs more justification. in language acquisition in particular, it is still in question whether the faculty is necessary or not. we succeeded in explaining one constraint on language acquisition in terms of a general learning mechanism. this paper describes a machine learning system rhea applied to the domain of language acquisition and shows that rhea can learn the tendency which children confronting new words seem to have.
idiosyncratic gap: a tough problem to structure-bound machine translation. current practical machine translation system (mt, in short), which are designed to deal with a huge amount of document, are generally structure-bound. that is, the translation process is done based on the analysis and transformation of the structure of source sentence, not on the understanding and para-phrasing of the meaning of that. but each language has its own syntactic and semantic idiosyncrasy, and on this account, without understanding the total meaning of source sentences it is often difficult for mt to bridge properly the idiosyncratic gap between source- and target- language. a somewhat new method called "cross translation test (ctt, in short)" is presented that reveals the detail of idiosyncratic gap (ig, in short) together with the so-so satisfiable possibility of mt. it is also mentioned the usefulness of sublanguage approach to reducing the ig between source- and target- language.
a proper treatmemt of syntax and semantics in machine translation. a proper treatment of syntax and semantics in machine translation is introduced and discussed from the empirical viewpoint. for english-japanese machine translation, the syntax directed approach is effective where the heuristic parsing model (hpm) and the syntactic role system play important roles. for japanese-english translation, the semantics directed approach is powerful where the conceptual dependency diagram (cdd) and the augmented case marker system (which is a kind of semantic role system) play essential roles. some examples of the difference between japanese sentence structure and english sentence structure, which is vital to machine translation, are also discussed together with various interesting ambiguities.
corpus-based generation of numeral classifier using phrase alignment. a severe problem for nlp applications dealing with multilingual language resources is the acquisition of knowledge that is obligatory in one language but not explicitly expressed in another language. in this paper, we focus on numeral classifiers, which are required in languages like japanese but are usually not explicitly used in languages like english, which don't have such a classifier system.we propose a uniform method to assign the numeral classifiers of languages that have a numeral classifier system to the numerals of non-classifier languages. the omitted classifier information is extracted from a bilingual corpus based on phrasal correspondences in the contexts of the respective sentences.
a heuristic approach to english-into-japanese machine translation. practical machine translation must be considered from a heuristic point of view rather than from a purely rigid analytical linguistic method. an english-into-japanese translation system named athene based on a heuristic parsing model (hpm) has been developed. the experiment shows some advantageous points such as simplification of transforming and generating phase, semilocalization of multiple meaning resolution, and extendability for future grammatical refinement. hpm-base parsing process, parsed tree, grammatical data representation, and translation results are also described.
aspects of pattern-matching in data-oriented parsing. data-oriented parsing (dop) ranks among the best parsing schemes, pairing state-of-the art parsing accuracy to the psycholinguistic insight that larger chunks of syntactic structures are relevant grammatical and probabilistic units. parsing with the dop-model, however, seems to involve a lot of cpu cycles and a considerable amount of double work, brought on by the concept of multiple derivations, which is necessary for probabilistic processing, but which is not convincingly related to a proper linguistic backbone. it is however possible to reinterpret the dop-model as a pattern-matching model, which tries to maximize the size of the substructures that construct the parse, rather than the probability of the parse. by emphasizing this memory-based aspect of the dop-model, it is possible to do away with multiple derivations, opening up possibilities for efficient viterbistyle optimizations, while still retaining acceptable parsing accuracy through enhanced context-sensitivity.
tagging spoken language using written language statistics. this paper reports on two experiments with a probabilistic part-of-speech tagger, trained on a tagged corpus of written swedish, being used to tag a corpus of (transcribed) spoken swedish. the results indicate that with very little adaptations an accuracy rate of 85% can be achieved, with an accuracy rate for known words of 90%. in addition, two different treatments of pauses were explored but with no significant gain in accuracy under either condition.
co-occurrence vectors from corpora vs. distance vectors from dictionaries. a comparison was made of vectors derived by using ordinary co-occurrence statistics from large text corpora and of vectors derived by measuring the interword distances in dictionary definitions. the precision of word sense disambiguation by using co-occurrence vectors from the 1987 wall street journal (20m total words) was higher than that by using distance vectors from the collins english dictionary (60k head words + 1.6m definition words). however, other experimental results suggest that distance vectors contain some different semantic information from co-occurrence vectors.
conceptual analysis of garden-path sentences. by integrating syntactic and semantic processing, our parser (lazy) is able to deterministically parse sentences which syntactically appear to be garden path sentences although native speakers do not need conscious reanalysis to understand them. lazy comprises an extension to conceptual analysis which yields an explicit representation of syntactic information and a flexible interaction between semantic and syntactic knowledge.
automatic semantic sequence extraction from unrestricted non-tagged texts. mophological processing, syntactic parsing and other useful tools have been proposed in the field of natural language processing (nlp). many of those nlp tools take dictionary-based approaches. thus these tools are often not very efficient with texts written in casual wordings or texts which contain many domain-specific terms, because of the lack of vocabulary.in this paper we propose a simple method to obtain domain-specific sequences from unrestricted texts using statistical information only. this method is language-independent.we had experiments on sequence extraction on email texts in japanese, and succeeded in extracting significant semantic sequences in the test corpus. we tried morphological parsing on the test corpus with chasen, a japanese dictionary-based morphological parser, and examined our system's efficiency in extraction of semantic sequences which were not recognized with chasen. our system detected 69.06% of the unknown words correctly.
probabilistic unification-based integration of syntactic and semantic preferences for nominal compounds. in this paper, we describe a probabilistic framework for unification-based grammars that facilitates integrating syntactic and semantic constraints and preferences. we share many of the concerns found in recent work on massively-parallel language interpretation models, although the proposal reflects our belief in the value of a higher-level account that is not stated in terms of distributed computation. we also feel that inadequate learning theories severely limit existing massively-parallel language interpretation models. a learning theory is not only interesting in its own right, but must underlie any quantitative account of language interpretation, because the complexity of interaction between constraints and preferences makes ad hoc trial-and-error strategies for picking numbers infeasible, particularly for semantics in realistically-sized domains.
segmenting sentences into linky strings using d-bigram statistics. it is obvious that segmentation takes an important role in natural language processing(nlp), especially for the languages whose sentences are not easily separated into morphemes. in this study we propose a method of segmenting a sentence. the system described in this paper does not use any grammatical information or knowledge in processing. instead, it uses statistical information drawn from non-tagged corpus of the target language. most of the segmenting systems are to pick out conventional morphemes which is defined for human use. however, we still do not know whether those conventional morphemes are good units for computational processing.in this paper we explain our system's algorithm and its experimental results on japanese, though this system is not designed for a particular language.
a comparison of alignment models for statistical machine translation. in this paper, we present and compare various alignment models for statistical machine translation. we propose to measure the quality of an alignment model using the quality of the viterbi alignment compared to a manually-produced alignment and describe a refined annotation scheme to produce suitable reference alignments. we also compare the impact of different alignment models on the translation quality of a statistical machine translation system.
prepositional phrase attachment through a hybrid disambiguation model. prepositional phrase attachment is a major cause of structural ambiguity in natural language. recent work has been dependent on corpus-based approaches to deal with this problem. however, corpus-based approaches suffer from the sparse-data problem. to cope with this problem, we introduce a hybrid method of integrating corpus-based approach with knowledge-based techniques, using a wide-variety of information that comes from annotated corpora and a machinere-adable dictionary. when the occurrence frequency on the corpora is low, we use preference rules to determine pp attachment based on clues from conceptual information. an experiment has proven that our hybrid method is both effective and applicable in practice.
segmenting a sentence into morpiiemes using statistic information between words. this paper is on dividing non-separated language sentences (whose words are not separated from each other with a space or other separaters) into morphemes using statistical information, not grammatical information which is often used in nlp. in this paper we describe our method and experimental result on japanese and chinese sentences. as will be seen in the body of this paper, the result shows that this system is efficient for most of the sentences.
parsing with look-ahead in real-time on-line translation system. in order to increase parsing efficiency in a real-time on-line translation system interfaced with a keyboard conversation program, we have developed a version of the atn formalism with a look-ahead function. by permitting future input to be scanned, arcs can be reordered or suppressed. various mechanisms utilizing this capability are presented.
taxonomy learning - factoring the structure of a taxonomy into a semantic classification decision. the paper examines different possibilities to take advantage of the taxonomic organization of a thesaurus to improve the accuracy of classifying new words into its classes. the results of the study demonstrate that taxonomic similarity between nearest neighbors, in addition to their distributional similarity to the new word, may be useful evidence on which classification decision can be based.
formal properties of rule orderings in linguistics. the discovery in the late 1960's that standard linguistic theory (of chomsky's <u>aspects</u>) was equivalent in generative power to unrestricted rewrite rules caused linguists to search for a "stronger linguistic metatheory". it seemed to some of these researchers that this meant describing linguistic theory by means of rules which were more restricted than type 0 languages. such a view we call the l-view of constraints on linguistic theory: it advocates constraining the allowable rules in such a way that legitimate grammars can no longer generate arbitrary r.e. sets, but only some subset of them. to other researchers this discovery meant rather that one should place restrictions on linguistic theory so that the kinds of grammars allowed would be limited, regardless of whether such limitations affected the generative power of the theory. we call this the g-view of constraints. the l- and g-views are not equivalent limitations. for example, a g-view limitation on the class of regular grammars that any legitimate grammar be right-embedding is not thereby a l-view limitation, since this does not effect an alteration in generative power of the grammars allowed. the g-view is avowedly psychological; according to it, the point of placing constraints on grammars is to lessen directly the language learner's burden of choosing the correct grammar from all the possible ones. for the l-view, this is a side effect of disallowing whole classes of grammars in the first place.
machine translation by case generalization. case-based machine translation is a promising approach to resolving problems in rule-based machine translation systems, such as difficulties in control of rules and low adaptability to specific domains. we propose a new mechanism for case-based machine translation, in which a large set of cases is generalized into a smaller set of cases by using a thesaurus.
two theories for computing the logical form of mass expressions. there are various difficulties in accomodating the traditional mass/count distinction into a grammar for english which has a goal the production of "logical form" semantic translations of the initial english sentences. the present paper surveys some of these difficulties. one puzzle is whether the distinction is a syntactic one or a semantic one, i.e., whether it is a well-formedness constraint or whether it is a description of the semantic translations produced. another puzzle is whether it should be applied to simple words (as they occur in the lexicon) or whether it should apply only to longer units (such as entire nps). of the wide variety of possible theories, only two seem to produce the required results (having to do with plausible inferences and intuitively satisfying semantic representations). these two theories are developed and compared.
a grammatico-statistical approach to discourse partitioning. the paper presents a new approach to text segmentation - which concerns dividing a text into coherent discourse units. the approach builds on the theory of discourse segment (nomoto and nitta, 1993), incorporating ideas from the research on information retrieval (salton, 1988). a discourse segment has to do with a structure of japanese discourse; it could be thought of as a linguistic unit demarcated by wa, a japanese topic particle, which may extend over several sentences. the segmentation works with discourse segments and makes use of coherence measure based on tf-idf, a standard information retrieval measurement (salton, 1988; hearst, 1993). experiments have been done with a japanese newspaper corpus. it has been found that the present approach is quite successful in recovering articles from the unstructured corpus.
investigating the relationship between word segmentation performance and retrieval performance in chinese ir. it is commonly believed that word segmentation accuracy is monotonically related to retrieval performance in chinese information retrieval. in this paper we show that, for chinese, the relationship between segmentation and retrieval performance is in fact nonmonotonic; that is, at around 70% word segmentation accuracy an over-segmentation phenomenon begins to occur which leads to a reduction in information retrieval performance. we demonstrate this effect by presenting an empirical investigation of information retrieval on chinese trec data, using a wide variety of word segmentation algorithms with word segmentation accuracies ranging from 44% to 95%. it appears that the main reason for the drop in retrieval performance is that correct compounds and collocations are preserved by accurate segmenters, while they are broken up by less accurate (but reasonable) segmenters, to a surprising advantage. this suggests that words themselves might be too broad a notion to conveniently capture the general semantic meaning of chinese text.
an empirical architecture for verb subcategorization frame - a lexicon for a real-world scale japanese-english interlingual mt. the verb subcategorization frame information plays a major role of disambiguations in many nlp applications. japanese, however, imposes difficulties of subcategorizing in part because it allows arbitrary ellipses of case elements. we propose a new type of verb subcategorization frame code set that combines the verb's surface case set and the deep case set, as a solution to the difficulties of empirical researches on japanese. the lexicon developed by this design has comprehensive information on the correspondences between the surface case frame and the deep case frame, and yet restrains the potential combinatorial explosion of the number of verb subcategorization frames by carefully identifying superficially different frames with an idea of alternative case markers and semantic roles, and by introducing the notion of surface case frame permutations. the number of different surface/deep case mapping types is 250, after we completed the new subcategorization frame code development for 30,000 verbs and adjectives.
translation by understanding: a machine translation system lute. this paper presents a linguistic model for language understanding and describes its application to an experimental machine translation system called lute. the language understanding model is an interactive model between the memory structure and a text. the memory structure is hierarchical and represented in a frame-network. linguistic and non-linguistic knowledge is stored and the result of understanding the text is assimilated into the memory structure. the understanding process is interactive in that the text invokes knowledge and the understanding proceduro interprets the text by using that knowledge. a linguistic model, called the extended case structure model, is defined by adopting three kinds of information: structure, relation and concept. these three are used recursively and iteratively as the basis for memory organization. these principles are applied to the design and implementation of the lute which translates japanese into english and vice vorsa.
the semantics of grammar formalisms seen as computer languages. the design, implementation, and use of grammar formalisms for natural language have constituted a major branch of computational linguistics throughout its development. by viewing grammar formalisms as just a special case of computer languages, we can take advantage of the machinery of denotational semantics to provide a precise specification of their meaning. using dana scott's domain theory, we elucidate the nature of the feature systems used in augmented phrase-structure grammar formalisms, in particular those of recent versions of generalized phrase structure grammar, lexical functional grammar and patr-ii, and provide a denotational semantics for a simple grammar formalism. we find that the mathematical structures developed for this purpose contain an operation of feature generalization, not available in those grammar formalisms, that can be used to give a partial account of the effect of coordination on syntactic features.
reversible unification based machine translation. in this paper it will be shown how unification grammars can be used to build a reversible machine translation system.unification grammars are often used to define the relation between strings and meaning representations in a declarative way. such grammars are sometimes used in a bidirectional way, thus the same grammar is used for both parsing and generation. in this paper i will show how to use bidirectional unification grammars to define reversible relations between language dependent meaning representations. furthermore it is shown how to obtain a completely reversible mt system using a series of (bidirectional) unification grammars.
a linguistic discovery program that verbalizes its discoveries. we describe a discovery program, called univauto (universals authoringtool), whose domain of application is the study of language universals, a classic trend in contemporary linguistics. accepting as input information about languages, presented in terms of feature-values, the discoveries of another human agent arising from the same data, as well as some additional data, the program discovers the universals in the data, compares them with the discoveries of the human agent and, if appropriate, generates a report in english on its discoveries. running univauto on the data from the seminal paper of greenberg (1966) on word order universals, the system has produced several linguistically valuable texts, two of which are published in a refereed linguistic journal.
adjuncts and the processing of lexical rules. the standard hpsg analysis of germanic verb clusters can not explain the observed narrowscope readings of adjuncts in such verb clusters.we present an extension of the hpsg analysis that accounts for the systematic ambiguity of the scope of adjuncts in verb cluster constructions, by treating adjuncts as members of the subcat list. the extension uses powerful recursive lexical rules, implemented as complex constraints. we show how 'delayed evaluation' techiniques from constraint-logic programming can be used to process such lexical rules.
handling syntactical ambiguity in machine translation. the difficulties to be met with the resolution of syntactical ambiguity in mt can be at least partially overcome by means of preserving the syntactical ambiguity of the source language into the target language. an extensive study of the correspondences between the syntactically ambiguous structures in english and bulgarian has provided a solid empirical basis in favor of such an approach. similar results could be expected for other sufficiently related languages as well. the paper concentrates on the linguistic grounds for adopting the approach proposed.