Topic
Phrase
About: Phrase is a research topic. Over the lifetime, 12580 publications have been published within this topic receiving 317823 citations. The topic is also known as: syntagma & phrases.
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10 Aug 2015
TL;DR: This paper investigates entity recognition (ER) with distant-supervision and proposes a novel relation phrase-based ER framework, called ClusType, that runs data-driven phrase mining to generate entity mention candidates and relation phrases, and enforces the principle that relation phrases should be softly clustered when propagating type information between their argument entities.
Abstract: Entity recognition is an important but challenging research problem. In reality, many text collections are from specific, dynamic, or emerging domains, which poses significant new challenges for entity recognition with increase in name ambiguity and context sparsity, requiring entity detection without domain restriction. In this paper, we investigate entity recognition (ER) with distant-supervision and propose a novel relation phrase-based ER framework, called ClusType, that runs data-driven phrase mining to generate entity mention candidates and relation phrases, and enforces the principle that relation phrases should be softly clustered when propagating type information between their argument entities. Then we predict the type of each entity mention based on the type signatures of its co-occurring relation phrases and the type indicators of its surface name, as computed over the corpus. Specifically, we formulate a joint optimization problem for two tasks, type propagation with relation phrases and multi-view relation phrase clustering. Our experiments on multiple genres---news, Yelp reviews and tweets---demonstrate the effectiveness and robustness of ClusType, with an average of 37% improvement in F1 score over the best compared method.
107 citations
TL;DR: The abstractness of lexical knowledge and its independence from the words of a language are generally underestimated as mentioned in this paper, and the learning burden of these two abstract but learned features of lexico-knowledge falls ouside of what current thinking about language learning would allow.
107 citations
TL;DR: It is argued that grammatical categories constitute an organizing parameter of representation and/or processing for each of the independent, modality-specific lexicons and that these observations contribute to the growing evidence that access to the orthographic and phonological forms of words can occur independently.
107 citations
TL;DR: This paper investigated the relationship between syntactic and prosodic phrase structures in the production and perception of spontaneous speech and found that syntax influences prosody production, listeners' perception of prosodic boundaries is sensitive to acoustic duration, and syntax directly influences boundary perception.
Abstract: The relationship between syntactic and prosodic phrase structures is investigated in the production and perception of spontaneous speech. Three hypotheses are tested: (1) syntax influences prosody production; (2) listeners' perception of prosodic boundaries is sensitive to acoustic duration; and (3) syntax directly influences boundary perception, (partly) independent of the acoustic evidence for boundaries. Data are from the Buckeye corpus of conversational speech, and the real-time prosodic transcription of those data by 97 untrained listeners. Inter-transcriber agreement codes boundary strength at word junctures, and Boundary scores are shown to be correlated with both the syntactic context and vowel duration of a word. Vowel duration is also correlated with syntactic context, but the effect of syntactic context on boundary perception is not fully explained by vowel duration. Regression analyses show that syntactic clause boundaries and vowel duration are the first and second strongest predictors of bou...
107 citations
07 Jul 1997
TL;DR: The results support the need to distinguish homonymy and polysemy and suggest where natural language processing can provide further improvements in retrieval performance.
Abstract: This paper discusses research on distinguishing word meanings in the context of information retrieval systems. We conducted experiments with three sources of evidence for making these distinctions: morphology, part-of-speech, and phrases. We have focused on the distinction between homonymy and polysemy (unrelated vs. related meanings). Our results support the need to distinguish homonymy and polysemy. We found: 1) grouping morphological variants makes a significant improvement in retrieval performance, 2) that more than half of all words in a dictionary that differ in part-of-speech are related in meaning, and 3) that it is crucial to assign credit to the component words of a phrase. These experiments provide better understanding of word-based methods, and suggest where natural language processing can provide further improvements in retrieval performance.
107 citations