waashk/dblp huggingface dataset:
structural correspondence specification environment. this article presents the structural correspondence specification environment (scse) being implemented at geta.the scse is designed to help linguists to develop, consult and verify the scs grammars (scsg) which specify linguistic models. it integrates the techniques of data bases, structured editors and language interpreters. we argue that formalisms and tools of specification are as important as the specification itself.
tree adjoining and head wrapping. in this paper we discuss the formal relationship between thw classes of languages generated by tree adjoining grammars and head grammars. in particular, we show that head languages are included in tree adjoining languages and that tree adjoining grammars are equivalent to a modification of head grammars called modified head grammars. the inclusion of mhl in hl, and thus the equivalence of hg's and tag's in the most general case remains to be established.
finite-state phrase parsing by rule sequences. we present a novel approach to parsing phrase grammars based on eric brill's notion of rule sequences. the basic framework we describe has somewhat less power than a finite-state machine, and yet achieves high accuracy on standard phrase parsing tasks. the rule language is simple, which makes it easy to write rules. further, this simplicity enables the automatic acquisition of phrase-parsing rules through an error-reduction strategy.
issues in word choice. this paper discusses word choice for natural language generation. it examines 11 issues, the solutions that have been proposed for them, and their implications for design. the issues are:how are appropriate words chosen?how is conciseness ensured?when does choice stop?how are patterns of lexicalization respected?how are interactions among choices handrled?how are the correct parts of speech chosen?how are words chosen to satisfy constituency?what ensures that a word stands in the correct relation to its neighbors?how is word order determined?are all words chosen in the same way?in what order are the factors considered?this paper also discusses fig, a generator which incorporates novel solutions to many of these issues. fig violates common assumptions about the roles of modularity and grammar in generator design. analysis of fig leads to 4 principles for generator design, as follows:have an explicit representation of the status of the generation process at each point in time.use a single, unified representation.do not rely on the details of the structure of the input.treat most choices as emergent.
using sentence connectors for evaluating mt output. this paper elaborates on the design of a machine translation evaluation method that aims to determine to what degree the meaning of an original text is preserved in translation, without looking into the grammatical correctness of its constituent sentences. the basic idea is to have a human evaluator take the sentences of the translated text and, for each of these sentences, determine the semantic relationship that exists between it and the sentence immediately preceding it. in order to minimise evaluator dependence, relations between sentences are expressed in terms of the conjuncts that can connect them, rather than through explicit categories. for an n-sentence text this results in a list of n-1 sentence-to-sentence relationships, which we call the text's connectivity profile. this can then be compared to the connectivity profile of the original text, and the degree of correspondence between the two would be a measure for the quality of the translation.a set of "essential" conjuncts was extracted for english and japanese, and a computer interface was designed to support the task of inserting the most fitting conjuncts between sentence pairs. with these in place, several sets of experiments were performed.
an alternative to deep case for representing relational information. no one has come up with a completely satisfactory set of deep cases relations (or thematic relations). the underlying reason is that any finite set of case relations can capture only some of the generalizations desired. i propose instead a feature-space representation of relational information, where the axes are such things as degree of responsibility, degree of activity, and degree of affectedness. the role of a participant in an event can then be described as a point in this space, allowing more accurate representation of relational information. the domain of validity of each relevant linguistic generalizations corresponds to a prototype-centered region in the space. this proposal is easy to implement.
a method for accelerating cfg-parsing by using dependency information. this paper describes an algorithm for accelerating the cfg-parsing process by using dependency (or modifier-modifiee relationship) information given by, for instance, dependency estimation programs such as stochastic parsers, user's indication in an interactive application, and linguistic annotations added in a source text. this is a method for enhancing existing grammar-based cfg-parsing system by using dependency information.
a similarity-driven transfer system. the transfer phase in machine translation (mt) systems has been considered to be more complicated than analysis and generation, since it is inherently a conglomeration of individual lexical rules. currently some attempts are being made to use case-based reasoning in machine translation, that is, to make decisions on the basis of translation examples at appropriate points in mt. this paper proposes a new type of transfer system, called a similarity-driven transfer system (sim tran), for use in such case-based mt (cbmt).
a method for distinguishing exceptional and general examples in example-based transfer systems. distinguishing exceptional translation examples is an important issue in example-based transfer systems, because such systems use exceptional and general translation examples uniformly. this paper describes a mechanism for dealing with exceptional translation examples in our example-based transfer system, simtran, and proposes a method for identifying such examples in a translation example-base.
a method for abstracting newspaper articles by using surface clues. this paper describes a system which automatically creates an abstract of a newspaper article by selecting important sentences of a given text. to determine the importance of a sentence, several superficial features are considered, and weights for features are determined by multiple-regression analysis of a hand processed corpus.
finding structural correspondences from bilingual parsed corpus for corpus-based translation. in this paper, we describe a system and methods for finding structural correspondences from the paired dependency structures of a source sentence and its translation in a target language. the system we have developed finds word correspondences first, then finds phrasal correspondences based on word correspondences. we have also developed a gui system with which a user can check and correct the correspondences retrieved by the system. these structural correspondences will be used as raw translation patterns in a corpus-based translation system.
document classification using domain specific kanji characters extracted by x2 method. in this paper we describe a method of classifying japanese text documents using domain specific kanji characters. text documents are generally classified by significant words (keywords) of the documents. however, it is difficult to extract these significant words from japanese text, because japanese texts are written without using blank spaces, such as delimiters, and must be segmented into words. therefore, instead of words, we used domain specific kanji characters which appear more frequently in one domain than the other. we extracted these domain specific kanji characters by x2 method. then, using these domain specific kanji characters, we classified editorial columns "tensei jingo", editorial articles, and articles in "scientific american (in japanese)". the correct recognition scores for them were 47%, 74%, and 85%, respectively.
an annotation system for enhancing quality of natural language processing. natural language processing (nlp) programs are confronted with various difficulties in processing html and xml documents, and have the potential to produce better results if linguistic information is annotated in the source texts. we have therefore developed the linguistic annotation language (or lal), which is an xml-compliant tag set for assisting natural language processing programs, and nlp tools such as parsers and machine translation programs which can accept lal-annotated input. in addition, we have developed a lal-annotation editor which allows users to annotate documents graphically without seeing tags. further, we have conducted an experiment to check the translation quality improvement by using lal annotation.
bidirectional decoding for statistical machine translation. this paper describes the right-to-left decoding method, which translates an input string by generating in right-to-left direction. in addition, presented is the bidirectional decoding method, that can take both of the advantages of left-to-right and right-to-left decoding method by generating output in both ways and by merging hypothesized partial outputs of two directions. the experimental results on japanese and english translation showed that the right-to-left was better for englith-to-japanese translation, while the left-to-right was suitable for japanese-to-english translation. it was also observed that the bidirectional method was better for english-to-japanese translation.
free adjuncts in natural language instructions. in this paper, we give a brief account of our project animation from instructions, the view of instructions it reflects, and the semantics of one construction - the free adjunct - that is common in natural language instructions.
tokenization as the initial phase in nlp. in this paper, the authors address the significance and complexity of tokenization, the beginning step of nlp. notions of word and token are discussed and defined from the viewpoints of lexicography and pragmatic implementation, respectively. automatic segmentation of chinese words is presented as an illustration of tokenization. practical approaches to identification of compound tokens in english, such as idioms, phrasal verbs and fixed expressions, are developed.
a concept of derivation for lfg. in this paper a version of lfg will be developed, which has only one level of representation and is equivalent to the modified version of [2], presented in [3]. the structures of this monostratal version are f-structures, augmented by additional information about the derived symbols and their linear order. for these structures it is possible to define an adequate concept of direct derivability by which the derivation process becomes more efficient, as the f-description solution algorithm is directly simulated during the derivation of these structures, instead of being postponed. apart from this it follows from this reducability that lfg as a theory in its present form does not make use of the c-structure information that goes beyond the mere linear order of the derived symbols.
generation as structure driven derivation. this paper describes two algorithms which construct two different types of generators for lexical functional grammars (lfgs). the first type generates sentences from functional structures and the second from semantic structures. the latter works on the basis of oxtended lfgs, which contain a mapping from f-structures into semantic structures. both algorithms can be used on all grammars within the respective class of lfg-grammars. thus sentences can be generated from input structures by means of lfg-grammars and the same grammar formalism, although not necessarily the same grammar, can be used for both analysis and synthesis.
on inference-based procedures for lexical disambiguation. in this paper we sketch a decidable inference-based procedure for lexical disambiguation which operates on semantic representations of discourse and conceptual knowledge. in contrast to other approaches which use a classical logic for the disambiguating inferences and run into decidability problems, we argue on the basis of empirical evidence that the underlying inference mechanism has to be essentially incomplete in order to the (cognitively) adequate. since our conceptual knowledge can be represented in a rather restricted representation language, it is then possible to show that the restrictions satisfied by the conceptual knowledge and the inferences ensure in an empirically adequate way the decidability of the problem, although a fully expressive language is used to represent discourse.
sts: an experimental sentence translation system. sts is a small experimental sentence translation system developed to demonstrate the efficiency of our lexicalist model of translation. based on a gb-inspired parser, lexical transfer and lexical projection, sts provides real-time accurate english translations for a small but non-trivial subset of french sentences.
the ips system. the ips system is a large-scale interactive gb-based parsing system (english, french) under development at the university of geneva. this paper starts with an overview of the system, discussing some of its basic features as well as its general architecture. we then turn to a more detailed discussion of the "right corner" parsing strategy developed for this project. combining top down and bottom up features, this strategy is consistent with an incremental interpretation of sentences.
automatic english-to-korean text translation of telegraphic messages in a limited domain. this paper describes our work-in-progress in automatic english-to-korean text translation. this work is an initial step toward the ultimate goal of text and speech translation for enhanced multilingual and multinational operations. for this purpose, we have adopted an interlingua approach with natural language understanding (tina) and generation (genesis) modules at the core. we tackle the ambiguity problem by incorporating syntactic and semantic categories in the analysis grammar. our system is capable of producing accurate translation of complex sentences (38 words) and sentence fragments as well as average length (12 words) grammatical sentences. two types of system evaluation have been carried out: one for grammar coverage and the other for overall performance. for system robustness, integration of two subsystems is under way: (i) a rule-based part-of-speech tagger to handle unknown words/constructions, and (ii) a word-forword translator to handle other system failures.
using constraints in a constructive version of gpsg. complex categories are caracteristic of unification grammars as for example gpsg [shieber86a]. they are sets of pairs of features and values. the unification, which can be applied to two or more categories, is the essential operation.the papers of [shieber85], [barton85] and [ristad86] deal with the influence of complex categories on the efficiency of the parsing algorithm. this is one problem from using complex categories, another one arises when using a constructive version of gpsg (see [busemann/hauenschild88] in this volume). namely that the application of admissibility conditions, e.g. lp statements and fcrs1, to a local tree t is prevented because particular feature values of categories in t are not yet specified, but they will be instantiated later somewhere else in the complete tree. similar problems are described in [karttunen86] for d-patr.this work describes the latter problem and will present a solution working with computation, evaluation and propagation of constraints within local trees (depth 1). the constraint evaluation will reject local trees if the constraints of the subtrees of the daughters are violated.
term-rewriting as a basis for a uniform architecture in machine translation. in machine translation (mt) different levels of representation can be used to translate a source language sentence onto its target language equivalent. these levels have to be related to each other. this paper describes a declarative formalism on the basis of term-rewriting which maps one representation onto an equivalent adjacent one. the different levels (e.g. represented by derivational trees, feature structures or expressions of a knowledge representation language) can be represented as terms. the equivalences between them are stated as axioms which are directed to form a non-confluent and terminating term-rewrite system. a complete and coherent algorithm has been developed which interprets these systems and is able to handle default rules.
direct parsing with metarules. in this paper we argue for the direct application of metarules in the parsing process and introduce a slight restriction on metarules. this restriction relies on theoretical results about the termination of term-rewrite systems and does not reduce the expressive power of metarules as much as previous restrictions. we prove the termination for a set of metarules used in our german grammar and show how metarules can be integrated into the parser.
selforganizing classification on the reuters news corpus. in this paper we propose an integration of a selforganizing map and semantic networks from wordnet for a text classification task using the new reuters news corpus. this neural model is based on significance vectors and benefits from the presentation of document clusters. the hypernym relation in wordnet supplements the neural model in classification. we also analyse the relationships of news headlines and their contents of the new reuters corpus by a series of experiments. this hybrid approach of neural selforganization and symbolic hypernym relationships is successful to achieve good classification rates on 100,000 full-text news articles. these results demonstrate that this approach can scale up to a large real-world task and show a lot of potential for text classification.
learning dialog act processing. in this paper we describe a new approach for learning dialog act processing. in this approach we integrate a symbolic semantic segmentation parser with a learning dialog act network. in order to support the unforeseeable errors and variations of spoken language we have concentrated on robust data-driven learning. this approach already compares favorably with the statistical average plausibility method, produces a segmentation and dialog act assignment for all utterances in a robust manner, and reduces knowledge engineering since it can be bootstrapped from rather small corpora. therefore, we consider this new approach as very promising for learning dialog act processing.
a formal computational semantics and pragmatics of speech acts. this paper outlines a formal computational semantics and pragmatics of the major speech act types. a theory of force is given that allows us to give a semantically and pragmaticaly motivated taxonomy of speech acts. the relevance of the communication theory to complex distribution artificial intellince, dai, systems is described.
conceptual structures and ccc: linking theory and incorporated argument adjuncts. in combinatory categorial grammar (ccg) [ste90, ste91], semantic function-argument structures are compositionally produced through the course of a derivation. these structures identify, inter alia, which entities play the same roles in different events for expressions involving a wide range of coordinate constructs. this sameness of role (i.e. thematic) information is not identified, however, across cases of verbal diathesis. to handle these cases as well, the present paper demonstrates how to adapt the solution developed in conceptual semantics [jac90, jac91] to fit the ccg paradigm.the essence of the approach is to redefine the linking theory component of conceptual semantics in terms of ccg categories, so that derivations yield conceptual structures representing the desired thematic information; in this way no changes are required on the ccg side. while this redefinition is largely straightforward, an interesting problem arises in the case of conceptual semantics' incorporated argument adjuncts. in examining these, the paper shows that they cannot be treated as adjuncts in the ccg sense without introducing new machinery, nor without compromising the independence of the two theories. for this reason, the paper instead adopts the more traditional approach of treating them as oblique arguments.
a graph model for unsupervised lexical acquisition. this paper presents an unsupervised method for assembling semantic knowledge from a part-of-speech tagged corpus using graph algorithms. the graph model is built by linking pairs of words which participate in particular syntactic relationships. we focus on the symmetric relationship between pairs of nouns which occur together in lists. an incremental cluster-building algorithm using this part of the graph achieves 82% accuracy at a lexical acquisition task, evaluated against wordnet classes. the model naturally realises domain and corpus specific ambiguities as distinct components in the graph surrounding an ambiguous word.
identifying subjective characters in narrative. part of understanding fictional narrative text is determining for each sentence whether it takes some character's point of view and, if it does, identifying the character whose point of view is taken. this paper presents part of an algorithm for performing the latter. when faced with a sentence that takes a character's point of view, the reader has to decide whether that character is a previously mentioned character or one mentioned in the sentence. we give particular consideration to sentences about private states, such as seeing and wanting, for which both possibilities exist. our algorithm is based on regularities in the ways that texts initiate, continue, and resume a character's point of view, found during extensive examinations of published novels and short stories.
reversible delayed lexical choice in a bidirectional framework. we describe a bidirectional framework for natural language parsing and generation, using a typed feature formalism and an hpsg-based grammar with a parser and generator derived from parallel processing algorithms. we present an approach to delayed lexical choice in generation, based on subsumption within the sort hierarchy, using a lexicon of under-instantiated signs which are derived from the normal lexicon by lexical rules. we then show how delayed lexical choice can be used in parsing, so that some types of ill-formed inputs can be parsed, but well-formed outputs are generated, using the same shared linguistic information.
extending the lexicon by exploiting subregularities. this paper is concerned with the acquisition of the lexicon. in particular, we propose a method that uses analogical reasoning to hypothesize new polysemous word senses. this method is one of a number of knowledge acquisition devices to be included in dirc (domain independent retargetable consultant). dirc is a kind of intelligent, natural language-capable consultant kit that can be retargeted at different domains. dirc is essentially "empty-uc" (unix consultant, wilensky et al., 1988). dirc is to include the language and reasoning mechanisms of uc, plus a large grammar and a general lexicon. the user must then add domain knowledge, user knowledge and lexical knowledge for the area of interest.
using a hybrid system of corpus- and knowledge-based techniques to automate the induction of a lexical sublanguage grammar. porting a natural language processing (nlp) system to a new domain remains one of the bottleneeks in syntactic parsing, because of the amount of effort required to fix gaps in the lexicon, and to attune the existing grammar to the idiosyncracies of the new sublanguage. this paper shows how the process of fitting a lexicalized grammar to a domain can be automated to a great extent by using a hybrid system that combines traditional knowledge-based techniques with a corpus-based approach.