waashk/dblp huggingface dataset:
anaphora resolution of japanese zero pronouns with deictic reference. this paper proposes a method to resolve the reference of deictic japanese zero pronouns which can be implemented in a practical machine translation system. this method focuses on semantic and pragmatic constraints such as semantic constraints on cases, modal expressions, verbal semantic attributes and conjunctions to determine the deictic refernce of japanese zero pronouns. this method is highly effective because the volume of knowledge that must be prepared before-hand is not very large and its precision of resolution is good. this method was implemented in the japanese-to-english machine translation system, alt-j/e. according to a window test for 175 zero pronouns with deictic referent in a sentence set for the evaluation of japanese-to-english machine translation systems, all of zero pronouns could be resolved consistently and correctly.
a system of verbal semantic attributes focused on the syntactic correspondence between japanese and english. this paper proposes a system of 97 verbal semantic attributes for japanese verbs which considers both dynamic characteristics and the relationship of verbs to cases. these attribute values are used to disambiguate the meanings of all japanese and english pattern pairs in a japanese to english transfer pattern dictionary consisting of 15,000 pairs of japanese valence patterns and equivalent english syntactic structures.
language model adaptation with additional text generated by machine translation. statistical language modeling requires a large corpus for the application domain. when a large corpus is not available, the language model adaptation technique has often been used in the speech recognition research domain. this adaptation needs only a small corpus of the application domain (the "target corpus") and the corpus should be written in the language of the model. however, it is sometimes difficult to collect even a small corpus, especially of spoken language, due to its high cost. to address this problem, this paper proposes a novel scheme that generates a small target corpus in the language of the model by machine translation of the target corpus in another language. as information about adjacent words, which is necessary for a statistical language model, is stored in the translation knowledge, it can be extracted by machine translation and used for adaptation. experiments showed that the language model improvement was about half of that which was obtained with a human collected corpus, and this provided some initial proof of the concept experiments.
neural network approach to word category prediction for english texts. word category prediction is used to implement an accurate word recognition system. traditional statistical approaches require considerable training data to estimate the probabilities of word sequences, and many parameters to memorize probabilities. to solve this problem, netgram, which is the neural network for word category prediction, is proposed. training results show that the performance of the netgram is comparable to that of the statistical model although the netgram requires fewer parameters than the statistical model. also the netgram performs effectively for unknown data, i.e., the netgram interpolates sparse training data. results of analyzing the hidden layer show that the word categories are classified into linguistically significant groups. the results of applying the netgram to hmm english word recognition show that the netgram improves the word recognition rate from 81.0% to 86.9%
extraction of semantic information from an ordinary english dictionary and its evaluation. the automatic extraction of semantic information especially semantic relationships between words, from an odinary english dictionary is described. for the extraction, the magnetic tape version of ldoce (longman dictionary of contemporary english, 1978 edition) is loaded into a relational database system. developed extraction programs analyze a definition sentence in ldoce with a pattern matching based algorithm. since this algorithm is not perfect, the result of the extraction has been compared with semantic information (semantic markers) which the magnetic tape version of ldoce contains. the result of comparison is also discussed for evaluating the reliability of such an automatic extraction.
grammar writing system (grade) of mu-machine translation project and its characteristics. a powerful grammar writing system has been developed. this grammar writing system is called grade (grammar describer). grade allows a grammar writer to write grammars including analysis, transfer, and generation using the same expression. grade has powerful grammar writing facility. grade allows a grammar writer to control the process of a machine translation. grade also has a function to use grammatical rules written in a word dictionary. grade has been used for more than a year as the software of the machine translation project from japanese into english, which is supported by the japanese government and called mu-project.
taking account of the user's view in 3d multimodal instruction dialogue. while recent advancements in virtual reality technology have created a rich communication interface linking humans and computers, there has been little work on building dialogue systems for 3d virtual worlds. this paper proposes a method for altering the instruction dialogue to match the user's view in a virtual environment. we illustrate the method with the system mid-3d, which interactively instructs the user on dismantling some parts of a car. first, in order to change the content of the instruction dialogue to match the user's view, we extend the refinement-driven planning algorithm by using the user's view as a plan constraint. second, to manage the dialogue smoothly, the system keeps track of the user's viewpoint as part of the dialogue state and uses this information for coping with interruptive subdialogues. these mechanisms enable mid-3d to set instruction dialogues in an incremental way; it takes account of the user's view even when it changes frequently.
a grammar and a parser for spontaneous speech. this paper classifies distinctive phenomena occurring in japanese spontaneous speech, and proposes a grammar and processing techniques for handling them. parsers using a grammar for written sentences cannot deal with spontaneous speech because in spontaneous speech there are phenomena that do not occur in written sentences. a grammar based on analysis of transcripts of dialogues was therefore developed. it has two distinctive features: it uses short units as input units instead of using sentences in grammars for written sentences, and it covers utterances including phrases peculiar to spontaneous speech. since the grammar is an augmentation of a grammar for written sentences, it can also be used to analyze complex utterances. incorporating the grammar into the distributed natural language processing model described elsewhere enables the handling of utterances including variety of phenomena peculiar to spontaneous speech.
topic detection based on dialogue history. in this paper, we propose a topic detection method using a dialogue history for a speech translator. the method uses a k-nearest neighbor method for the algorithm, automatically clusters target topics into smaller topics grouped by similarity, and incorporates dialogue history weighted in terms of time to detect and track topics on spoken phrases. from the evaluation of detection performance using test data comprised of realistic spoken dialogue, the method has shown to perform better with clustering incorporated, and when combined with dialogue history of three sentences, gives detection accuracy of 72.1%.
content-oriented categorization of document images. we have developed a technique that categorizes document images based on their content. unlike conventional methods that use optical character recognition (ocr), we convert document images into word shape takens, a shape-based representation of words. because we have only to recognize simple graphical features from image, this process is much faster than ocr. although the mapping between word shape tokens and words is one-to-many, they are a rich source of information for content characterization. using a vector space classifier with a scanned document image database, we show that the word shape token-based approach is quite adequate for content-oriented categorization in terms of accuracy compared with conventional ocr-based approaches.
error-tolerant tree matching. this paper presents an efficient algorithm for retrieving from a database of trees, all trees that match a given query tree approximately, that is, within a certain error tolerance. it has natural language processing applications in searching for matches in example-based translation systems, and retrieval from lexical databases containing entries of complex feature structures. the algorithm has been implemented on sparcstations, and for large randomly generated synthetic tree databases (some having tens of thousands of trees) it can associatively search for trees with a small error, in a matter of tenths of a second to few seconds.
a constraint-based case frame lexicon. we present a constraint-based case frame lexicon architecture for bi-directional mapping between a syntactic case frame and a semantic frame. the lexicon uses a semantic sense as the basic unit and employs a multi-tiered constraint structure for the resolution of syntactic information into the appropriate senses and/or idiomatic usage. valency changing transformations such as morphologically marked passivized or causativized forms are handled via lexical rules that manipulate case frames templates. the system has been implemented in a typed-feature system and applied to turkish.
interaction with a limited object domain - zapsib project. the report presents the basic principles of the zapsib project aimed at the development of a modular series of linguistic processors designed for natural language (nl) interaction with applied data bases. the general structure of the zapsib processors and functions of the main modules are discussed, as well as technology of the project including problem of processors adaptation to an object domain of the interaction.
the knowledge representation for a story understanding and simulation system. there exist many difficult problems to understand a situation and an event described in sentences or a story. one of them is to treat with more than one subject and their relations. another is the comprehension of movement of the subjects and their effects to the others. in this pater, micro-actor is used as the knowledge representation in which such the problems mentioned above are solved. the micro-actor is an artificial intelligence module for knowledge representation, which is realized hewitt's actor concept.a large problem is often solved by a group of specialists. each specialist has his own knowledge and technique. a specialist can accomplish independently a small work communicating with the others. the specialist is implemented in the form of micro-actor on a computer. the micro-actor is independent of the others, and communicating with the others using one kind of action: sending message to another micro-actor.we discuss the following four problems to understand stories and the approaches to them: (1) depth of understanding sentences to comprehend a story, (2) a method to deal with an event which happens on the specific condition, (3) synchronization of the events which occur at same time and (4) treatment of the event which involves more than one object.
robust method of pronoun resolution using full-text information. a consistent text contains rich information for resolving ambiguities within its sentences. even simple syntactic information such as word occurrence and collocation patterns, which can be extracted from the text without deep discourse analysis, improves the accuracy of sentence analysis. pronoun resolution is a typical proceeding that utilizes this information. through the use of this information, along with information on the syntactic position of each candidate, 93.8% of pronoun references were resolved correctly in an experiment on computer manuals.
full-text processing: improving a practical nlp system based on surface information within the context. rich information for resolving ambiguities in sentence analysis, including various context-dependent problems, can be obtained by analyzing a simple set of parsed trees of each sentence in a text without constructing a precise model of the context through deep semantic analysis. thus, processing a group of sentences together makes it possible to improve the accuracy of a practical natural language processing (nlp) system such as a machine translation system. in this paper, we describe a simple context model consisting of parsed trees of each sentence in a text, and its effectiveness for handling various problems in nlp such as the resolution of structural ambiguities, pronoun referents, and the focus of focusing subjects (e.g. also and only), as well as for adding supplementary phrases to some elliptical sentences.
a new parallel algorithm for generalized lr parsing. tomita's parsing algorithm [tomita 86], which adapted the lr parsing algorithm to context free grammars, makes use of a breadth-first strategy to handl lr table conflicts. as the breadth-first strategy is compatible with parallel processing, we can easily develop a parallel generalized lr parser based on tomita's algorithm [tanaka 89]. however, there is a problem in that this algorithm synchronizes parsing processes on each shift action for the same input word to merge many stacks into graph structured stacks (gss). in other words, a process that has completed a shift action must wait until all other processes have ended theirs --- a strategy that reduces parallel performance. we have developed a new parallel parsing algorithm that does not need to wait for shift actions before merging many stacks, using stream communication of a concurrent logic programming language called ghc [ueda 85]. thus we obtain a parallel generalized lr parser implemented in ghc.
the morphological analysis of bahasa malaysia. this paper describes a model for the automated morphological analysis of bahasa malaysia (the malay language) via the atef system, a component of the mechanical translation system known as ariane, which was developed by g.e.t.a. at grenoble. this model serves two purposes, that is, to test the capability of handling bahasa malaysia morphological analysis using atef and also to provide a first workign model.
the kant system: fast, accurate, high-quality translation in practical domains. knowledge-based interlingual machine translation systems produce semantically accurate translations, but typically require massive knowledge acquisition. ongoing research and development at the center for machine translation has focussed on reducing this requirement to produce large-scale practical applications of knowledge-based mt. this paper describes kant, the first system to combine principled source language design, semi-automated knowledge acquisition, and knowledge compilation techniques to produce fast, high-quality translation to multiple languages.
semantic and syntactic aspects of score function. in a machine translation system (mts), the number of possible analyses for a given sentence is largely due to the ambiguous characteristics of the source language. in this paper, a mechanism, called "score function", is proposed for measuring the "quality" of the ambiguous syntax trees such that the one that best fits interpretation by human is selected. it is featured by incorporating the objectiveness of the probability theory and the subjective expertise of linguists. the underlying uncertainty that is fundamental to linguistic knowledge is also allowed to be incorporated into this system. this feature proposes an easy resolution to select the best syntax tree and provides some strategic advantages for scored parsing. the linguists can also be relieved of the necessity to describe the language in strictly "correct" linguistic rules, which, if not impossible, is a very hard task.
two-way finite automata and dependency grammar: a parsing method for inflectional free word order languages. this paper presents a parser of an inflectional free word order language, namely finnish. two-way finite automata are used to specify a functional dependency grammar and to actually parse finnish sentences. each automaton gives a functional description of a dependency structure within a constituent. dynamic local control of the parser is realized by augmenting the automata with simple operations to make the automata, associated with the words of an input sentence, activate one another.
tools for extracting and structuring knowledge from texts. we demonstrate an approach and an accompanying unix toolbox for performing various kinds of knowledge extractions and structuring. the goal is to "practically" enhance the productivity while constructing resources for nlp systems on the basis of large corpora of technical texts., users are lexicon/grammar builders, terminologists and knowledge engineers. we stay open to already explored methods in this or neighbouring activities but put a greater stress on the use of linguistic knowledge. the originality of the work presented here lies in the scope of applications addressed and in the degree of use of linguistic knowledge.
querying temporal databases using controlled natural language. recent years have shown a surge in interest in temporal database systems, which allow users to store time-dependent information. we present a novel controlled natural language interface to temporal databases, based on translating natural language questions into sql/temporal, a temporal database query language. the syntactic analysis is done using the type-logical grammar framework, highlighting its utility not only as a theoretical framework but also as a practical tool. the semantic analysis is done using a novel theory of the semantics of temporal questions, focusing on the role of temporal preposition phrases rather than the more traditional focus on tense and aspect. our translation method is considerably simpler than previous attempts in this direction. we present a prototype software implementation.
an english-korean transliteration model using pronunciation and contextual rules. there is increasing concern about english-korean (e-k) transliteration recently. in the previous works, direct converting methods from english alphabets to korean alphabets were a main research topic. in this paper, we present an e-k transliteration model using pronunciation and contextual rules. unlike the previous works, our method uses phonetic information such as phoneme and its context. we also use word formation information such as english words of greek origin, with them, our method shows significant performance increase about 31% in word accuracy.
glosser-rug: in support of reading. this paper reports on ongoing work on a call system to facilitate foreign language learning: glosser-rug. the system is particularly dependent on advanced morphological analysis. following a brief introduction to the project, the paper describes the architecture of glosser-rug. then we describe in detail the main components/modules that are part of the implemented prototype. finally, implementation issues and details involving the user interfaces of the tool are discussed. we outline the design of an integrated system to support the reading of french text by dutch speakers.
restricted parallelism in object-oriented lexical parsing. we present an approach to parallel natural language parsing which is based on a concurrent, object-oriented model of computation. a depth-first, yet incomplete parsing algorithm for a dependency grammar is specified and several restrictions on the degree of its parallelization are discussed.
syntactic functions in gpsg. this paper motivates and proposes adding a new feature of <u>syntactic function</u> to the feature system of gpsg. later, it shows its necessity in number of syntactic constructs, such as passivization, extraposition, coordination etc. but adding such feature is not understood as a mere technicality, and thus some implications for the explanatory power of the theory are also discussed.
a head-driven approach to incremental and parallel generation of syntactic structures. this paper describes the construction of syntactic structures within an incremental multi-level and parallel generation system. incremental and parallel generation imposes special requirements upon syntactic description and processing. a head-driven grammar represented in a unification-based formalism is introduced which satisfies these demands. furthermore the basic mechanisms for the parallel processing of syntactic segments are presented.
simple parser for an hpsg-style grammar implemented in prolog. this paper describes basic ideas of a parser for hpsg style grammars without lp component. the parser works bottom-up using the left corner method and a chart for improving efficiency. attention is paid to the format of grammar rules as required by the parser, to the possibilities of direct implementation of principles of the grammar as well as to solutions of problems connected with storing partly specified categories in the chart.
self-monitoring with reversible grammars. we describe a method and its implementation for self-monitoring during natural language generation. in situations of communication where the generation of ambiguous utterances should be avoided our method is able to compute an unambiguous utterance for a given semantic input. the proposed method is based on a very strict integration of parsing and generation. during the monitored generation step, a previously generated (possibly) ambiguous utterance is parsed and the obtained alternative derivation trees are used as a 'guide' for re-generating the utterance. to achieve such an integrated approach the underlying grammar must be reversible.
the proper treatment of word order in hpsg. this paper describes a possibility of expressing ordering constraints among non-sister constituents in binary branching syntactic structures on a local basis, supported by viewing the binary branching structure as a list (rather than a tree) of constitutents within hpsg-style grammars. the core idea of such a description of ordering is constituted by creating a type lattice for lists. the possibilities of expressing different approaches to word order in the framework are briefly discussed, exemplified and compared to other methods.
towards convenient bi-directional grammar formalisms. this paper discusses the advantages for practical bi-directional grammars of combining a lexical focus with the gpsg-originated principle of immediate-dominance/linear-precedence (id/lp) rule partitioning. it also outlines an implementation approach following these guidelines. the approach is inspired by slot grammar, with additions including more explicit mappings between surface and internal representations, and preferential constituent ordering rules.
identifying concepts across languages: a first step towards a corpus-based approach to automatic ontology alignment. the growing importance of multilingual information retrieval and machine translation has made multilingual ontologies an extremely valuable resource. since the construction of an ontology from scratch is a very expensive and time consuming undertaking, it is attractive to consider ways of automatically aligning monolingual ontologies, which already exist for many of the world's major languages.
list automata with syntactically structured output. a new type of abstract automaton is introduced, and both formal and linguistic implications are discussed, most importantly a new possibility of proving certain formal properties of (natural) languages and their grammars (such as context-freeness) and of refinement of the chomsky hierarchy.