Summary stringlengths 55 2.67k | Text stringlengths 45 130k | Id stringlengths 8 8 |
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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... | 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 |
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... | 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 |
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... | 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 |
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 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 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... | 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 |
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... | 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 |
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... | 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 |
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 ... | 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 |
"a novel use of statistical parsing to extract information from textsince 1995 a few statistical par(...TRUNCATED) | "a novel use of statistical parsing to extract information from text since 1995 a few statistical pa(...TRUNCATED) | A00-2030 |
"assigning function tags to parsed textit is generally recognized that the common nonterminal labels(...TRUNCATED) | "assigning function tags to parsed text and vincent j della pietra 1996 a maximum entropy approach t(...TRUNCATED) | A00-2031 |
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