{"title":"Foundations of Intensional Semantics","authors":"","doi":"10.1162/coli.2006.32.2.291","DOIUrl":"https://doi.org/10.1162/coli.2006.32.2.291","url":null,"abstract":"From the combination of knowledge and actions, someone can improve their skill and ability. It will lead them to live and work much better. This is why, the students, workers, or even employers should have reading habit for books. Any book will give certain knowledge to take all benefits. This is what this foundations of intensional semantics tells you. It will add more knowledge of you to life and work better. Try it and prove it.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117092055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Generating Natural Language Summaries from Multiple On-Line Sources","authors":"Dragomir R. Radev, K. McKeown","doi":"10.7916/D83N2B7J","DOIUrl":"https://doi.org/10.7916/D83N2B7J","url":null,"abstract":"We present a methodology for summarization of news about current events in the form of briefings that include appropriate background (historical) information. The system that we developed, SUMMONS, uses the output of systems developed for the DARPA Message Understanding Conferences to generate summaries of multiple documents on the same or related events, presenting similarities and differences, contradictions, and generalizations among sources of information. We describe the various components of the system, showing how information from multiple articles is combined, organized into a paragraph, and finally, realized as English sentences. A feature of our work is the extraction of descriptions of entities such as people and places for reuse to enhance a briefing.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129817622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Floating Constraints in Lexical Choice","authors":"Michael Elhadad, K. McKeown, J. Robin","doi":"10.7916/D82V2S0J","DOIUrl":"https://doi.org/10.7916/D82V2S0J","url":null,"abstract":"Lexical choice is a computationally complex task, requiring a generation system to consider a potentially large number of mappings between concepts and words. Constraints that aid in determining which word is best come from a wide variety of sources, including syntax, semantics, pragmatics, the lexicon, and the underlying domain. Furthermore, in some situations, different constraints come into play early on, while in others, they apply much later. This makes it difficult to determine a systematic ordering in which to apply constraints. In this paper, we present a general approach to lexical choice that can handle multiple, interacting constraints. We focus on the problem of floating constraints, semantic or pragmatic constraints that float, appearing at a variety of different syntactic ranks, often merged with other semantic constraints. This means that multiple content units can be realized by a single surface element, and conversely, that a single content unit can be realized by a variety of surface elements. Our approach uses the Functional Unification Formalism (FUF) to represent a generation lexicon, allowing for declarative and compositional representation of individual constraints.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115007248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Machine Transliteration","authors":"Kevin Knight, Jonathan Graehl","doi":"10.3115/976909.979634","DOIUrl":"https://doi.org/10.3115/976909.979634","url":null,"abstract":"It is challenging to translate names and technical terms across languages with different alphabets and sound inventories. These items are commonly transliterated, i.e., replaced with approximate phonetic equivalents. For example, computer in English comes out as (konpyuutaa) in Japanese. Translating such items from Japanese back to English is even more challenging, and of practical interest, as transliterated items make up the bulk of text phrases not found in bilingual dictionaries. We describe and evaluate a method for performing backwards transliterations by machine. This method uses a generative model, incorporating several distinct stages in the transliteration process.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124679940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discourse Segmentation by Human and Automated Means","authors":"R. Passonneau, D. Litman","doi":"10.5555/972684.972689","DOIUrl":"https://doi.org/10.5555/972684.972689","url":null,"abstract":"The need to model the relation between discourse structure and linguistic features of utterances is almost universally acknowledged in the literature on discourse. However, there is only weak consensus on what the units of discourse structure are, or the criteria for recognizing and generating them. We present quantitative results of a two-part study using a corpus of spontaneous, narrative monologues. The first part of our paper presents a method for empirically validating multitutterance units referred to as discourse segments. We report highly significant results of segmentations performed by naive subjects, where a commonsense notion of speaker intention is the segmentation criterion. In the second part of our study, data abstracted from the subjects' segmentations serve as a target for evaluating two sets of algorithms that use utterance features to perform segmentation. On the first algorithm set, we evaluate and compare the correlation of discourse segmentation with three types of linguistic cues (referential noun phrases, cue words, and pauses). We then develop a second set using two methods: error analysis and machine learning. Testing the new algorithms on a new data set shows that when multiple sources of linguistic knowledge are used concurrently, algorithm performance improves.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115581260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Translating Collocations for Bilingual Lexicons: A Statistical Approach","authors":"Frank Smadja, K. McKeown, V. Hatzivassiloglou","doi":"10.7916/D8C82M3R","DOIUrl":"https://doi.org/10.7916/D8C82M3R","url":null,"abstract":"Collocations are notoriously difficult for non-native speakers to translate, primarily because they are opaque and cannot be translated on a word-by-word basis. We describe a program named Champollion which, given a pair of parallel corpora in two different languages and a list of collocations in one of them, automatically produces their translations. Our goal is to provide a tool for compiling bilingual lexical information above the word level in multiple languages, for different domains. The algorithm we use is based on statistical methods and produces p-word translations of n-word collocations in which n and p need not be the same. For example, Champollion translates make...decision, employment equity, and stock market into prendre...decision, equite en matiere d'emploi, and bourse respectively. Testing Champollion on three years' worth of the Hansards corpus yielded the French translations of 300 collocations for each year, evaluated at 73% accuracy on average. In this paper, we describe the statistical measures used, the algorithm, and the implementation of Champollion, presenting our results and evaluation.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131178322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Generative Lexicon","authors":"J. Pustejovsky","doi":"10.2307/415891","DOIUrl":"https://doi.org/10.2307/415891","url":null,"abstract":"In this paper, I will discuss four major topics relating to current research in lexical semantics: methodology, descriptive coverage, adequacy of the representation, and the computational usefulness of representations. In addressing these issues, I will discuss what I think are some of the central problems facing the lexical semantics community, and suggest ways of best approaching these issues. Then, I will provide a method for the decomposition of lexical categories and outline a theory of lexical semantics embodying a notion of cocompositionality and type coercion, as well as several levels of semantic description, where the semantic load is spread more evenly throughout the lexicon. I argue that lexical decomposition is possible if it is performed generatively. Rather than assuming a fixed set of primitives. I will assume a fixed number of generative devices that can be seen as constructing semantic expressions. I develop a theory of Qualia Structure, a representation language for lexical items, which renders much lexical ambiguity in the lexicon unnecessary, while still explaining the systematic polysemy that words carry. Finally, I discuss how individual lexical structures can be integrated into the larger lexical knowledge base through a theory of lexical inheritance. This provides us with the necessary principles of global organization for the lexicon, enabling us to fully integrate our natural language lexicon into a conceptual whole.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124546863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Indexical Expressions in the Scope of Attitude Verbs","authors":"A. Haas","doi":"10.5555/972500.972503","DOIUrl":"https://doi.org/10.5555/972500.972503","url":null,"abstract":"A sentential theory of attitudes holds that propositions (the things that agents believe and know) are sentences of a representation language. Given such a theory, it is natural to suggest that the proposition expressed by an utterance of natural language is also a sentence of a representation language. This leads to a straightforward account of the semantics of attitude verbs. However, this kind of theory encounters problems in dealing with indexicals: expressions such as \"I,\" \"here,\" and \"now.\" It is hard to explain how an indexical in the scope of an attitude verb can be opaque. This paper suggests that while the propositions that agents believe and know are sentences, the propositions expressed by utterances are not sentences: they are singular propositions, of the type used in Kaplan's theory of direct reference. Drawing on recent work in situation semantics, this paper shows how such a theory can describe the semantics of attitude verbs and account for the opacity of indexicals in the scope of these verbs.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132461217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Empirical Studies on the Disambiguation of Cue Phrases","authors":"Julia Hirschberg, D. Litman","doi":"10.7916/D8PV6TGB","DOIUrl":"https://doi.org/10.7916/D8PV6TGB","url":null,"abstract":"Cue phrases are linguistic expressions such as now and well that function as explicit indicators of the structure of a discourse. For example, now may signal the beginning of a subtopic or a return to a previous topic, while well may mark subsequent material as a response to prior material, or as an explanatory comment. However, while cue phrases may convey discourse structure, each also has one or more alternate uses. While incidentally may be used sententially as an adverbial, for example, the discourse use initiates a digression. Although distinguishing discourse and sentential uses of cue phrases is critical to the interpretation and generation of discourse, the question of how speakers and hearers accomplish this disambiguation is rarely addressed.This paper reports results of empirical studies on discourse and sentential uses of cue phrases, in which both text-based and prosodic features were examined for disambiguating power. Based on these studies, it is proposed that discourse versus sentential usage may be distinguished by intonational features, specifically, pitch accent and prosodic phrasing. A prosodic model that characterizes these distinctions is identified. This model is associated with features identifiable from text analysis, including orthography and part of speech, to permit the application of the results of the prosodic analysis to the generation of appropriate intonational features for discourse and sentential uses of cue phrases in synthetic speech.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128635709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mitchell P. Marcus, Beatrice Santorini, Mary Ann Marcinkiewicz
{"title":"Building a Large Annotated Corpus of English: The Penn Treebank","authors":"Mitchell P. Marcus, Beatrice Santorini, Mary Ann Marcinkiewicz","doi":"10.21236/ada273556","DOIUrl":"https://doi.org/10.21236/ada273556","url":null,"abstract":"Abstract : As a result of this grant, the researchers have now published oil CDROM a corpus of over 4 million words of running text annotated with part-of- speech (POS) tags, with over 3 million words of that material assigned skeletal grammatical structure. This material now includes a fully hand-parsed version of the classic Brown corpus. About one half of the papers at the ACL Workshop on Using Large Text Corpora this past summer were based on the materials generated by this grant.","PeriodicalId":360119,"journal":{"name":"Comput. Linguistics","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121284573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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