waashk/dblp huggingface dataset:
dckr - knowledge representation in prolog and its application to natural language processing. semantic processing is one of the important tasks for natural language processing. basic to semantic processing is descriptions of lexical items. the most frequently used form of description of lexical items is probably frames or objects. therefore in what form frames or objects are expressed is a key issue for natural language processing. a method of the object representation in prolog called dckr will be introduced. it will be seen that if part of general knowledge and a dictionary are described in dckr, part of context processing and the greater part of semantic processing can be left to the functions built in prolog.
verbal case frame acquisition from a bilingual corpus: gradual knowledge acquisition. this paper describes acquisition of english surface case frames from a corpus, based on a gradual knowledge acquisition approach. to acquire and unambiguously accumulate precise knowledge, the process is divided into three steps which are assigned to the most appropriate processor: either a human or a computer. the data is prepared by human workers and the knowledge is acquired and accumulated by a leaning program. by using this method, inconsistent human judgement is minimized. the acquired case frames basically duplicate human work, but are more precise and intelligible.
decision tree learning algorithm with structured attributes: application to verbal case frame acquisition. the decision tree learning algorithms (dtlas) are getting keen attention from the natural language processing research community, and there have been a series of attempts to apply them to verbal case frame acquisition. however, a dtla cannot handle structured attributes like nouns, which are classified under a thesaurus. in this paper, we present a new dtla that can rationally handle the structured attributes. in the process of tree generation, the algorithm generalizes each attribute optimally using a given thesaurus. we apply this algorithm to a bilingual corpus and show that it successfully learned a generalized decision tree for classifying the verb "take" and that the tree was smaller with more prediction power on the open data than the tree learned by the conventional dtla.
extraction of lexical translations from non-aligned corpora. a method for extracting lexical translations from non-aligned corpora is proposed to cope with the unavailability of large aligned corpus. the assumption that "translations of two co-occurring words in a source language also co-occur in the target language" is adopted and represented in the stochastic matrix formulation. the translation matrix provides the co-occurring information translated from the source into the target. this translated co-occurring information should resemble that of the original in the target when the ambiguity of the translational relation is resolved. an algorithm to obtain the best translation matrix is introduced. some experiments were performed to evaluate the effectiveness of the ambiguity resolution and the refinement of the dictionary.
construction of a bilingual dictionary intermediated by a third language. when using a third language to construct a bilingual dictionary, it is necessary to discriminate equivalencies from inappropriate words derived as a result of ambiguity in the third language. we propose a method to treat this by utilizing the structures of dictionaries to measure the nearness of the meanings of words. the resulting dictionary is a word-to-word bilingual dictionary of nouns and can be used to refine the entries and equivalencies in published bilingual dictionaries.
shallow language processing architecture for bulgarian. this paper describes lingua - an architecture for text processing in bulgarian. first, the pre-processing modules for tokenisation, sentence splitting, paragraph segmentation, part-of-speech tagging, clause chunking and noun phrase extraction are outlined. next, the paper proceeds to describe in more detail the anaphora resolution module. evaluation results are reported for each processing task.
syntactic analysis of natural language using linguistic rules and corpus-based patterns. we are concerned with the syntactic annotation of unrestricted text. we combine a rule-based analysis with subsequent exploitation of empirical data. the rule-based surface syntactic analyser leaves some amount of ambiguity in the output that is resolved using empirical patterns. we have implemented a system for generating and applying corpus-based patterns. some patterns describe the main constituents in the sentence and some the local context of the each syntactic function. there are several (partly) reduntant patterns, and the "pattern" parser selects analysis of the sentence that matches the strictest possible pattern(s). the system is applied to an experimental corpus. we present the results and discuss possible refinements of the method from a linguistic point of view.
restructuring tagged corpora with morpheme adjustment rules. a part-of-speech tagged corpus is a very important knowledge source for natural language processing researchers. today, several part-of-speech tagged corpora are readily available for research use. however, because there is wide diversity of morphological information systems (word-segmentation, part-of-speech system, etc.), it is difficult to use tagged corpora with an incompatible morphological information system. this paper proposes a method of converting tagged corpora from one morpheme system to another.
matching a tone-based and tune-based approach to english intonation for concept-to-speech generation. the paper describes the results of a comparison of two annotation systems for intonation, the tone-based tobi approach and the tune-based approach proposed by systemic functional grammar (sfg). the goal of this comparison is to define a mapping between the two systems for the purpose of concept-to-speech generation of english. since tobi is widely used in speech synthesis and sfg is widely used in natural language generation and offers a linguistically motivated account of intonation, it appears a promising step to combine the two approaches for concept-to-speech. a corpus of english utterances has been analysed with both tobi and sfg categories; comparison of the analysis results has lead to the identification of some basic equivalents between the two systems on which a mapping can be based.
quantification of meaning and the computer. one of the major tasks of the quantitative semantic analysis is to disclose complex relations of sememes in communication, i.e. on the basis of their associations in the frame of syntactic structures. with the aid of computer it is possible to prepare a corpus of language material giving the possibility to quantify /1./semantics of syntactic functions, /2./ lexical meanings, /3./ meanings of morphological categories, esp. those of parts of speech, and to create a new type of semantic frequency dictionary.
applications of a lexicographical data base for german. the institut f&uuml;r deutsche sprache recently has begun setting up a lexicographical data base for german (leda). this data base is designed to improve efficiency in the collection, analysis, ordering and description of language material by facilitating access to textual samples within corpora and to word articles within machine readable dictionaries and by providing a frame to store results of lexicographical research for further processing. leda thus consists of the three components text bank, dictionary bank and result bank and serves as a tool to support monolingual german dictionary projects at the institute and elsewhere.
automatic extraction of semantic relations from specialized corpora. in this paper we address the problem of discovering word semantic similarities via statistical processing of text corpora. we propose a knowledge-poor method that exploits the sentencial context of words for extracting similarity relations between them as well as semantic in nature word clusters. the approach aims at full portability across domains and languages and therefore is based on minimal resources.
multi-dimensional text classification. this paper proposes a multi-dimensional framework for classifying text documents. in this framework, the concept of multidimensional category model is introduced for representing classes. in contrast with traditional flat and hierarchical category models; the multi-dimensional category model classifies each text document in a collection using multiple predefined sets of categories, where each set corresponds to a dimension. since a multi-dimensional model can be converted to flat and hierarchical models, three classification strategies are possible, i.e., classifying directly based on the multi-dimensional model and classifying with the equivalent flat or hierarchical models. the efficiency of these three classifications is investigated on two data sets. using k-nn, na&iuml;ve bayes and centroid-based classifiers, the experimental results show that the multi-dimensional-based and hierarchical-based classification performs better than the flat-based classifications.
parsing for grammar and style checking. the following paper describes some basic problems which have to be tackled if a morphosyntactic parser is to be configured in a grammar and style checking environment. whereas grammar checking has to deal with ill-formed input which by definition is outside the scope of a grammar, style checking has problems in grammar coverage and intentionality of style.to overcome these problems, a method is presented based on the metal grammar formalism which allows for fallback rules, levelling and scoring mechanisms, and other features which can be used. it will be described what kinds of information and processing are needed to implement such checkers.finally, some examples are given which illustrate the mode of operation of the method described.
incorporating metaphonemes in a multilingual lexicon. this paper describes a framework for multilingual inheritance-based lexical representation which allows sharing of information across languages at all levels of linguistic description. the paper focuses on phonology. it explores the possibility of establishing a phoneme inventory for a group of languages in which language-specific phonemes function as "allophones" of newly defined metaphonemes. dutch, english, and german were taken as a test bed and their vowel phoneme inventories were studied. the results of the cross-linguistic analysis are presented in this paper. the paper concludes by showing how these metaphonemes can be incorporated in a multilingual lexicon.
learning to select a good translation. within the machine translation system verbmobil, translation is performed simultaneously by four independent translation modules. the four competing translations are combined by a selection module so as to form a single optimal output for each input utterance. the selection module relies on confidence values that are delivered together with each of the alternative translations. since the confidence values are computed by four independent modules that are fundamentally different from one another, they are not directly comparable and need to be rescaled in order to gain comparative significance. in this paper we describe a machine learning method tailored to overcome this difficulty by using off-line human feedback to determine an appropriate confidence rescaling scheme. additionally, we describe some other sources of information that are used for selecting between the competing translations, and describe the way in which the selection process relates to quality of service specifications.
word re-ordering and dp-based search in statistical machine translation. in this paper, we describe a search procedure for statistical machine translation (mt) based on dynamic programming (dp). starting from a dp-based solution to the traveling salesman problem, we present a novel technique to restrict the possible word reordering between source and target language in order to achieve an efficient search algorithm. a search restriction especially useful for the translation direction from german to english is presented. the experimental tests are carried out on the verbmobil task (german-english, 8000-word vocabulary), which is a limited-domain spoken-language task.
a type-theoretical analysis of complex verb generation. tense and aspect, together with mood and modality, usually form the entangled structure of a complex verb. they are often hard to translate by machines, because of both syntactic and semantic differences between languages. this problem seriously affects upon the generation process because those verb components in interlingua are hardly rearranged correctly in the target language. we propose here a method in which each verb element is defined as a mathematical function according to its type of type theory. this formalism gives each element its legal position in the complex verb in the target language and certifies so-called partial translation. in addition, the generation algorithm is totally free from the stepwise calculation, and is available on parallel architecture.
free-ordered cug on chemical abstract machine. we propose a paradigm for concurrent natural language generation. in order to represent grammar rules distributively, we adopt categorial unification grammar (cug) where each category owns its functional type. we augment typed lambda calculus with several new combinators, to make the order of &lambda;-conversions free for partial / local processing. the concurrent calculus is modeled with chemical abstract machine. we show an example of a japanese causative auxiliary verb that requires a drastic rearrangement of case domination.
quasi-destructive graph unification with structure-sharing. graph unification remains the most expensive part of unification-based grammar parsing. we focus on one speed-up element in the design of unification algorithms: avoidance of copying of unmodified subgraphs. we propose a method of attaining such a design through a method of structure-sharing which avoids log(d) overheads often associated with structure-sharing of graphs without any use of costly dependency pointers. the proposed scheme eliminates redundant copying while maintaining the quasi-destructive scheme's ability to avoid over copying and early copying combined with its ability to handle cyclic structures without algorithmic additions.
lr parsers for natural languages. mlr, an extended lr parser, is introduced, and its application to natural language parsing is discussed. an lr parser is a shift-reduce parser which is deterministically guided by a parsing table. a parsing table can be obtained automatically from a context-free phrase structure grammar. lr parsers cannot manage ambiguous grammars such as natural language grammars, because their parsing tables would have multiply-defined entries, which precludes deterministic parsing. mlr, however, can handle multiply-defined entries, using a dynamic programming method. when an input sentence is ambiguous, the mlr parser produces all possible parse trees without parsing any part of the input sentence more than once in the same way, despite the fact that the parser does not maintain a chart as in chart parsing. our method also provides an elegant solution to the problem of multi-part-of-speech words such as "that". the mlr parser and its parsing table generator have been implemented at carnegie-mellon university.
disambiguating grammatically ambiguous sentences by asking. the problem addressed in this paper is to disambiguate grammatically ambiguous input sentences by asking the user, who need not be a computer specialist or a linguist, without showing any parse trees or phrase structure rules. explanation list comparison (elc) is the technique that implements this process. it is applicable to all parsers which are based on phrase structure grammar, regardless of the parser implementation. an experimental system has been implemented at carnegie-mellon university, and it has been applied to english-japanese machine translation at kyoto university.
combining lexicon-driven parsing and phrase-structure-based parsing. lexicon-driven formalisms (e.g. categorial grammar; hpsg and gb grammar), which do not have explicit phrase structure rules, are suitable for higher level syntax but not for low level language-specific constructions such as dates (july 15th, 15-jul-1987, etc), which seem to require the power of phrase structure rules. this paper presents an implementation method to combine lexicon-driven parsing and phrase structure parsing, with a special means called graph-structured stack.
another stride towards knowledge-based machine translation. building on the well-established premise that reliable machine translation requires a significant degree of text comprehension, this paper presents a recent advance in multi-lingual knowledge-based machine translation (kbmt). unlike previous approaches, the current method provides for separate syntactic and semantic knowledge sources that are integrated dynamically for parsing and generation. such a separation enables the system to have syntactic grammars, language specific but domain general, and semantic knowledge bases, domain specific but language general. subsequently, grammars and domain knowledge are precompiled automatically in any desired combination to produce very efficient and very thorough real-time parsers. a pilot implementation of our kbmt architecture using functional grammars and entity-oriented semantics demonstrates the feasibility of the new approach.1
logical form of hierarchical relation on verbs and extracting it from definition sentences in a japanese dictionary. we are studying how to extract hierachical relation on verbs from definition sentences in a japanese dictionary. the hierarchical relation on verbs has been dealt with as a binary relation on verbs, but it should be dealt with as logical relation on predicates. we will define the logical form of the hierarchical relation on verbs and then discuss which part of the syntactic structure of the definition sentence represents that relation. we will call the main predicate verb in this part the definition verb. furthermore we will describe how to semiautomatically select the proper meaning of the definition verb and the proper correspondence between cases of an entry verb and the definition verb in order to extract the hierarchical relation as logical relation.
an explanation facility for a grammar writing system. explanation has become a standard feature in many expert systems today. adapting from this work, a study was made to determine the types of explanation required in a grammar writing system and to investigate design and implementation issues. the first version of this explanation facility is based on a derivational history of the inferencing process, and although no supplementary knowledge is used, this explanation facility is able to furnish answers to the traditional why, how and what type of queries, and even the what-if (simulation) query. the explanation is also enhanced through the use of special files containing canned-text for describing grammar rules and variables.
an unsupervised learning method for associative relationships between verb phrases. this paper describes an unsupervised learning method for associative relationships between verb phrases, which is important in developing reliable q&a systems. consider the situation that a user gives a query "how much petrol was imported by japan from saudi arabia?" to a q&a system, but the text given to the system includes only the description "x tonnes of petrol was conveyed to japan from saudi arabia." we think that the description is a good clue to find the answer for our query, "x tonnes." but there is no large-scale database that provides the associative relationship between "imported" and "conveyed." our aim is to develop an unsupervised learning method that can obtain such an associative relationship, which we call scenario consistency. the method we are currently working on uses an expectation-maximization (em) based word-clustering algorithm, and we have evaluated the effectiveness of this method using japanese verb phrases.
computing phrasal-signs in hpsg prior to parsing. this paper describes techniques to compile lexical entries in hpsg (pollard and sag, 1987; pollard and sag, 1993)-style grammar into a set of finite state automata. the states in automata are possible signs derived from lexical entries and contain information raised from the lexical entries. the automata are augmented with feature structures used by a partial unification routine and delayed/frozen definite clause programs.
linguistic contribution to text-to-speech computer programs for french. this paper presents the development of computer programs used for transcribing french text into phonetic speech. based on an earlier program (maggs & trescases, 1980) made of a set of some 500 text-to-phonetics rules and of a compact set of prosodic rules for synthetic speech, the present research was primarily aiming at developing the best possible algorithm to account for practically any word in the french general lexicon, as opposed to most frequently used words only. in order to considerably enhance the original rules, these were systematically tested against a 50, 000 word french pronunciation dictionary and an equally important corpus of texts which were all entered in an ibm pc-xt. at the same time, a set of syntactic rules was developed for most liaisons, mandatory and forbidden, and homographs to be found in french speech. the result is a set of some 4, 800 conversion rules. tested against the 50, 000 words of the pronunciation dictionary, they yield a low percentage of error. errors in text are similarly minimal, and due mainly to foreign (english) words. to allow faster programing, while accounting for most commonly used words in french, a compact set of 2, 000 rules has been developed. it is essentially based on a statistical analysis yielding most frequently used general rules. the aim of both algorithms has been to make possible better text-to-speech software for french.
the application of two-level morphology to non-concatenative german morphology. in this paper we describe a hybrid system for morphological analysis and synthesis. we call it hybrid because it consists of two separate parts interacting with each other in a well-defined way. the treatment of morphonology and non-concatenative morphology is based on the two-level approach originally proposed by koskenniemi (1983). for the concatenative part of morphosyntax (i.e. affixation) we make use of a grammar based on feature-unification. both parts rely on the same morph lexicon.combinations of two-level morphology with feature-based morphosyntactic grammars have already been proposed by several authors (c.f. bear 1988a, carson 1988, g&ouml;rz & paulus 1988, schiller & steffens 1990) to overcome the shortcomings of the continuation-classes originally proposed by koskenniemi (1983) and karttunen (1983) for the description of morphosyntax. but up to now no linguistically satisfying solution has been proposed for the treatment of non-concatenative morphology in such a framework. in this paper we describe an extension to the model which will allow for the description of such phenomena. namely we propose to restrict the applicability of two-level rules by providing them with filters in the form of feature structures. we demonstrate how a well-known problem of german morphology, so-called "umlautung", can be described in our approach in a linguistically motivated and efficient way.