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tnt a statistical partofspeech tagger trigramsntags is an efficient statistical partofspeech tagger contrary to claims found elsewhere in the literature we argue that a tagger based on markov models performs at least as well as other current approaches including the maximum entropy framework a recent comparison has e...	A00-1031	tnt a statistical partofspeech taggertrigramsntags is an efficient statistical partofspeech taggercontrary to claims found elsewhere in the literature we argue that a tagger based on markov models performs at least as well as other current approaches including the maximum entropy frameworka recent comparison has even...
sentence reduction for automatic text summarization figure 2 sample sentence and parse tree we have an input sentence t dg b4a because both the human and the program made decisions two out of the five decisions agree so the rate is 25 the rate defined as man and the program have made the same decision success rate t...	A00-1043	sentence reduction for automatic text summarizationwe present a novel sentence reduction system for automatically removing extraneous phrases from sentences that are extracted from a document for summarization purposethe system uses multiple sources of knowledge to decide which phrases in an extracted sentence can be r...
advances in domain independent linear text segmentation this paper describes a method for linear text segmentation which is twice as accurate and over seven times as fast as the stateoftheart intersentence similarity is replaced by rank in the local context boundary locations are discovered by divisive clustering even...	A00-2004	advances in domain independent linear text segmentationthis paper describes a method for linear text segmentation which is twice as accurate and over seven times as fast as the stateoftheart intersentence similarity is replaced by rank in the local contextboundary locations are discovered by divisive clusteringwe desig...
a simple approach to building ensembles of naive bayesian classifiers for word sense disambiguation this paper presents a corpusbased approach to word sense disambiguation that builds an ensemble of naive bayesian classifiers each of which is based on lexical features that represent cooccurring words in varying sized w...	A00-2009	a simple approach to building ensembles of naive bayesian classifiers for word sense disambiguationthis paper presents a corpusbased approach to word sense disambiguation that builds an ensemble of naive bayesian classifiers each of which is based on lexical features that represent cooccurring words in varying sized wi...
a maximumentropyinspired parser we present a new parser for parsing down to penn treebank style parse trees that achieves 901 average precisionrecall for sentences of 40 and less and for of length 100 and less when trained and tested on the previously established 59101517 quotstandardquot sections of the wall street jo...	A00-2018	a maximumentropyinspired parserwe present a new parser for parsing down to penn treebank style parse trees that achieves 901 average precisionrecall for sentences of length 40 and less and 895 for sentences of length 100 and less when trained and tested on the previously established 59101517 standard sections of the wa...
an unsupervised method for detecting grammatical errors we present an unsupervised method for detecting grammatical errors by inferring negative evidence from edited textual corpora the system was developed and tested using essaylength responses to prompts on the test of english as a foreign language the errorrecognit...	A00-2019	an unsupervised method for detecting grammatical errorswe present an unsupervised method for detecting grammatical errors by inferring negative evidence from edited textual corporathe system was developed and tested using essaylength responses to prompts on the test of english as a foreign language the errorrecognition...
cut and paste based text summarization we present a cut and paste based text summarizer which uses operations derived from an analysis of human written abstracts the summarizer edits extracted sentences using reduction to remove inessential phrases and combination to merge resulting phrases together as coherent sentenc...	A00-2024	cut and paste based text summarizationwe present a cut and paste based text summarizer which uses operations derived from an analysis of human written abstractsthe summarizer edits extracted sentences using reduction to remove inessential phrases and combination to merge resuiting phrases together as coherent sentences...
trainable methods for surface natural language generation we present three systems for surface natural language generation that are trainable from annotated corpora the first two systems called nlg1 and nlg2 require a corpus marked only with domainspecific semantic attributes while the last system called nlg3 requires ...	A00-2026	trainable methods for surface natural language generationwe present three systems for surface natural language generation that are trainable from annotated corporathe first two systems called nlg1 and nlg2 require a corpus marked only with domainspecific semantic attributes while the last system called nlg3 requires a ...
a novel use of statistical parsing to extract information from text since 1995 a few statistical parsing algorithms have demonstrated a breakthrough in parsing accuracy as measured against the upenn treebank as a gold standard in this paper we report adapting a lexic al ized probabilistic contextfree parser to informat...	A00-2030	a novel use of statistical parsing to extract information from textsince 1995 a few statistical parsing algorithms have demonstrated a breakthrough in parsing accuracy as measured against the upenn treebank as a gold standardin this paper we report adapting a lexicalized probabilistic contextfree parser to information ...
assigning function tags to parsed text and vincent j della pietra 1996 a maximum entropy approach to natural lanprocessing linguistics parsing sentences using statistical information gathered from a treebank was first examined a decade ago in and is by now a fairly wellstudied problem but to date the end product of ...	A00-2031	assigning function tags to parsed textit is generally recognized that the common nonterminal labels for syntactic constituents do not exhaust the syntactic and semantic information one would like about parts of a syntactic treefor example the penn treebank gives each constituent zero or more function tags indicating s...
using semantic preferences to identify verbal participation in role switching alternations we propose a method for identifying diathesis alternations where a particular argument type is seen in slots which have different grammatical roles in the alternating forms the method uses selectional preferences acquired as prob...	A00-2034	using semantic preferences to identify verbal participation in role switching alternationswe propose a method for identifying diathesis alternations where a particular argument type is seen in slots which have different grammatical roles in the alternating formsthe method uses selectional preferences acquired as probab...
a stochastic parts program and noun phrase parser for unrestricted text there are five missing brackets which are indicated as quotquot or quot1quot words with a second np tag were identified as proper nouns in a prepass aat formerap topnn aidenn toin attorneynpnp generalnpnp edwinnpnp meesenpnp intercededvbd toto exte...	A88-1019	a stochastic parts program and noun phrase parser for unrestricted textour part of speech tagger can now input unrestricted text and assign each word with the most likely part of speech with fairly reasonable accuracy and efficiencyour partofspeech tagger performs not only partofspeech analysis but it also identities t...
applied text generation this paper presents the joyce system as an example of a fullyimplemented applicationoriented text generation systemjoyce covers the whole range of tasks associated with text generation from content selection to morphological processingit was developped as part of the interface of the software d...	A92-1006	applied text generationwe divide tasks in the generation process into three stages the text planner has access only to information about communicative goals the discourse context and semantics and generates a nonlinguistic representation of text structure and content the sentence planner chooses abstract linguistic res...
a practical partofspeech tagger we present an implementation of a partofspeech tagger based on a hidden markov model the methodology enables robust and accurate tagging with few resource requirements only a lexicon and some unlabeled training text are required accuracy exceeds 96 we describe implementation strategies a...	A92-1018	a practical partofspeech taggerwe present an implementation of a partofspeech tagger based on a hidden markov modelthe methodology enables robust and accurate tagging with few resource requirementsonly a lexicon and some unlabeled training text are requiredaccuracy exceeds 96we describe implementation strategies and op...
a simple rulebased part of speech tagger automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rulebased methods in this paper we present a simple rulebased part of speech tagger which automatically acquires its rules and tags with accurac...	A92-1021	a simple rulebased part of speech taggerautomatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rulebased methodsin this paper we present a simple rulebased part of speech tagger which automatically acquires its rules and tags with accuracy ...
termight identifying and translating technical terminology 1993 we that part of speech tagging and word alignment could have an important role in glossary construction for translation glossaries are extremely important for translation how would microsoft or some other software vendor want the term quotcharacter menuquo...	A94-1006	termight identifying and translating technical terminologywe propose a semiautomatic tool termight that helps professional translators and terminologists identify technical terms and their translationsthe tool makes use of partofspeech tagging and wordalignment programs to extract candidate terms and their translations...
does baumwelch reestimation help taggers in part of speech tagging by hidden markov model a statistical model is used to assign grammatical categories to words in a text early work in the field relied on a corpus which had been tagged by a human annotator to train the model recently cutting al suggest that training can...	A94-1009	does baumwelch reestimation help taggersin part of speech tagging by hidden markov model a statistical model is used to assign grammatical categories to words in a textearly work in the field relied on a corpus which had been tagged by a human annotator to train the modelmore recently cutting et al suggest that traini...
three heads are better than one machinereadable dictionary the lexicons used by the kbmt modules a large set of usergenerated bilingual glossaries as well as a gazetteer and a list of proper and organization namesthe outputs from these engines are recorded in a chart whose positions correspond to words in the source...	A94-1016	three heads are better than onemachine translation systems do not currently achieve optimal quality translation on free text whatever translation method they employour hypothesis is that the quality of mt will improve if an mt environment uses output from a variety of mt systems working on the same textin the latest v...
a maximum entropy approach to identifying sentence boundaries we present a trainable model for identifying sentence boundaries in raw text given a corpus annotated with sentence boundaries our model learns to classify each occurrence of and as either a valid or invalid sentence boundary the training procedure requires...	A97-1004	a maximum entropy approach to identifying sentence boundarieswe present a trainable model for identify ing sentence boundaries in raw textgiven a corpus annotated with sentence boundaries our model learns to classify each occurrence of and as either a valid or invalid sentence boundarythe training procedure require...
a nonprojective dependency parser we describe a practical parser for unrestricted dependencies the parser creates links between words and names the links according to their syntactic functions we first describe the older constraint grammar parser where many of the ideas come from then we proceed to describe the central...	A97-1011	a nonprojective dependency parserwe describe a practical parser for unrestricted dependenciesthe parser creates links between words and names the links according to their syntactic functionswe first describe the older constraint grammar parser where many of the ideas come fromthen we proceed to describe the central ide...
an annotation scheme for free word order languages we describe an annotation scheme and a tool developed for creating linguistically annotated corpora for nonconfigurational languages since the requirements for such a formalism differ from those posited for configurational languages several features have been added inf...	A97-1014	an annotation scheme for free word order languageswe describe an annotation scheme and a tool developed for creating linguistically annotated corpora for nonconfigurational languagessince the requirements for such a formalism differ from those posited for configurational languages several features have been added influ...
nymble a highperformance learning namefinder this paper presents a statistical learned approach to finding names and other nonrecursive entities in text using a variant of the standard hidden markov model we present our justification for the problem and our approach a detailed discussion of the model itself and finall...	A97-1029	nymble a highperformance learning namefinderthis paper presents a statistical learned approach to finding names and other nonrecursive entities in text using a variant of the standard hidden markov modelwe present our justification for the problem and our approach a detailed discussion of the model itself and finally ...
disambiguation of proper names in text trieving information from full text using linguisknowledge in of the fifteenth online meeting new york may text processing applications such as machine translation systems information retrieval systems or naturallanguage understanding systems need to identify multiword expressions...	A97-1030	disambiguation of proper names in textidentifying the occurrences of proper names in text and the entities they refer to can be a difficult task because of the manytomany mapping between names and their referentswe analyze the types of ambiguity structural and semantic that make the discovery of proper names difficul...
a fast and portable realizer for text generation systems systems that generate natural language output as part of their interaction with a user have become a major area of research and developmenttypically natural language generation is divided into several phases namely text planning sentence planning and realizati...	A97-1039	a fast and portable realizer for text generation systemswe release a surface realizer realpro and it is intended as offtheshelf plugin realizerour realpro surface realizer which produces a surface linguistic utterance
automatic extraction of subcategorization from corpora of the system that are new the extractor classifier and evaluator the grammar consists of 455 phrase structure rule schemata in the format accepted by the parser operators it is hallow in that no atof which thetempt is made to fully analyse unbounded dependencies ...	A97-1052	automatic extraction of subcategorization from corporawe describe a novel technique and implemented system for constructing a subcategorization dictionary from textual corporaeach dictionary entry encodes the relative frequency of occurrence of a comprehensive set of subcategorization classes for englishan initial expe...
base noun phrase translation using web data and the them algorithm we consider here the problem of base noun phrase translation we propose a new method to perform the task for a given base np we first search its translation candidates from the web we next determine the possible translation from among the candidates usi...	C02-1011	base noun phrase translation using web data and the them algorithmwe consider here the problem of base noun phrase translationwe propose a new method to perform the taskfor a given base np we first search its translation candidates from the webwe next determine the possible translation from among the candidates using o...
efficient support vector classifiers for named entity recognition named entity recognition is a task in whichproper nouns and numerical information are extracted from documents and are classified into cat egories such as person organization and date it is a key technology of information extraction and opendomain quest...	C02-1054	efficient support vector classifiers for named entity recognitionnamed entity recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into categories such as person organization and dateit is a key technology of information extraction and opendomain questio...
a graph model for unsupervised lexical acquisition this paper presents an unsupervised method forassembling semantic knowledge from a partof speech tagged corpus using graph algorithms the graph model is built by linking pairs of words which participate in particular syntacticrelationships we focus on the symmetric rel...	C02-1114	a graph model for unsupervised lexical acquisitionthis paper presents an unsupervised method for assembling semantic knowledge from a partofspeech tagged corpus using graph algorithmsthe graph model is built by linking pairs of words which participate in particular syntactic relationshipswe focus on the symmetric relat...
concept discovery from text broadcoverage lexical resources such as wordnet are extremely useful however they often include many rare senses while missing domainspecific senses we present a clustering algorithm called cbc that automatically discovers concepts from text it initially discovers a set of tight clusters ca...	C02-1144	concept discovery from textbroadcoverage lexical resources such as wordnet are extremely usefulhowever they often include many rare senses while missing domainspecific senseswe present a clustering algorithm called cbc that automatically discovers concepts from textit initially discovers a set of tight clusters called...
building a largescale annotated chinese corpus in this paper we address issues related to building a largescale chinese corpus we try to answer four questions how to speed up annotation how to maintain high annotation quality for what purposes is the corpus applicable and finally what future work we anticipate the ...	C02-1145	building a largescale annotated chinese corpusin this paper we address issues related to building a largescale chinese corpuswe try to answer four questions how to speed up annotation how to maintain high annotation quality for what purposes is the corpus applicable and finally what future work we anticipate
learning question classifiers in order to respond correctly to a free form factual question given a large collection of texts one needs to un derstand the question to a level that allows determiningsome of the constraints the question imposes on a pos sible answer these constraints may include a semantic classification...	C02-1150	learning question classifiersin order to respond correctly to a free form factual question given a large collection of texts one needs to understand the question to a level that allows determining some of the constraints the question imposes on a possible answerthese constraints may include a semantic classification of...
deterministic dependency parsing of english text this paper presents a deterministic dependency parser based on memorybased learning which parses english text in linear time when trainedand evaluated on the wall street journal sec tion of the penn treebank the parser achieves a maximum attachment score of 871 unlikemos...	C04-1010	deterministic dependency parsing of english textthis paper presents a deterministic dependency parser based on memorybased learning which parses english text in linear timewhen trained and evaluated on the wall street journal section of the penn treebank the parser achieves a maximum attachment score of 871unlike most ...
efficient parsing of highly ambiguous contextfree grammars with bit vectors an efficient bitvectorbased ckystyle parser for contextfree parsing is presented the parser computes a compact parse forest representation of the complete set of possible analyses forlarge treebank grammars and long input sen tences the parser ...	C04-1024	efficient parsing of highly ambiguous contextfree grammars with bit vectorsan efficient bitvectorbased ckystyle parser for contextfree parsing is presentedthe parser computes a compact parse forest representation of the complete set of possible analyses for large treebank grammars and long input sentencesthe parser use...
the importance of supertagging for widecoverage ccg parsing this paper describes the role of supertagging in a widecoverage ccg parser which uses a loglinear model to select an analysis the supertagger reduces the derivation space over which model estimation is performed reducing the space required for discriminative t...	C04-1041	the importance of supertagging for widecoverage ccg parsingthis paper describes the role of supertagging in a widecoverage ccg parser which uses a loglinear model to select an analysisthe supertagger reduces the derivation space over which model estimation is performed reducing the space required for discriminative tra...
unsupervised construction of large paraphrase corpora exploiting massively parallel news sources we investigate unsupervised techniques for acquiring monolingual sentencelevel paraphrases from a corpus of temporally and topically clustered news articles collected from thousands of webbased news sources two techniques a...	C04-1051	unsupervised construction of large paraphrase corpora exploiting massively parallel news sourceswe investigate unsupervised techniques for acquiring monolingual sentencelevel paraphrases from a corpus of temporally and topically clustered news articles collected from thousands of webbased news sourcestwo techniques are...
language model adaptation for statistical machine translation via structured query models we explore unsupervised language model adaptation techniques for statistical machine translation the hypotheses from the machine translation output are converted into queries at different levels of representation power and used to...	C04-1059	language model adaptation for statistical machine translation via structured query modelswe explore unsupervised language model adaptation techniques for statistical machine translationthe hypotheses from the machine translation output are converted into queries at different levels of representation power and used to e...
orange a method for evaluating automatic evaluation metrics for machine translation comparisons of automatic evaluation metrics for machine translation are usually conducted on corpus level using correlation statistics such as pearsons product moment correlation coefficient or spearmans rank order correlation coefficie...	C04-1072	orange a method for evaluating automatic evaluation metrics for machine translationcomparisons of automatic evaluation metrics for machine translation are usually conducted on corpus level using correlation statistics such as pearsons product moment correlation coefficient or spearmans rank order correlation coefficie...
partofspeech tagging in context we present a new hmm tagger that exploits context on both sides of a word to be tagged and evaluate it in both the unsupervised and supervised case along the way we present the first comprehensive comparison of unsupervised methods for partofspeech tagging noting that published results t...	C04-1080	partofspeech tagging in contextwe present a new hmm tagger that exploits context on both sides of a word to be tagged and evaluate it in both the unsupervised and supervised casealong the way we present the first comprehensive comparison of unsupervised methods for partofspeech tagging noting that published results to ...
chinese segmentation and new word detection using conditional random fields chinese word segmentation is a difficult i am portant and widelystudied sequence modelingproblem this paper demonstrates the abil ity of linearchain conditional random fields to perform robust and accurate chinese word segmentation by providing...	C04-1081	chinese segmentation and new word detection using conditional random fieldschinese word segmentation is a difficult important and widelystudied sequence modeling problemthis paper demonstrates the ability of linearchain conditional random fields to perform robust and accurate chinese word segmentation by providing a p...
towards terascale semantic acquisition although vast amounts of textual data are freely available many nlp algorithms exploit only a minute percentage of it in this paper we study the challenges of working at the terascale we present an algorithm designed for the terascale for mining isa relations that achieves similar...	C04-1111	towards terascale semantic acquisitionalthough vast amounts of textual data are freely available many nlp algorithms exploit only a minute percentage of itin this paper we study the challenges of working at the terascalewe present an algorithm designed for the terascale for mining isa relations that achieves similar pe...