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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TL;DR: The cooccurrence and topographical dissimilarity of the "N200" and N400 suggest that the N400 may not be a delayed or a generic N200.
145 citations
Proceedings Article•
01 Nov 2011TL;DR: This paper collects and analyse the compositionality judgments for a range of compound nouns using Mechanical Turk, and evaluates two different types of distributional models for compositionality detection – constituent based models and composition function based models.
Abstract: A multiword is compositional if its meaning can be expressed in terms of the meaning of its constituents. In this paper, we collect and analyse the compositionality judgments for a range of compound nouns using Mechanical Turk. Unlike existing compositionality datasets, our dataset has judgments on the contribution of constituent words as well as judgments for the phrase as a whole. We use this dataset to study the relation between the judgments at constituent level to that for the whole phrase. We then evaluate two different types of distributional models for compositionality detection – constituent based models and composition function based models. Both the models show competitive performance though the composition function based models perform slightly better. In both types, additive models perform better than their multiplicative counterparts.
145 citations
TL;DR: The ChemicalTagger parser is developed as a medium-depth, phrase-based semantic NLP tool for the language of chemical experiments and it is possible parse to chemical experimental text using rule-based techniques in conjunction with a formal grammar parser.
Abstract: The primary method for scientific communication is in the form of published scientific articles and theses which use natural language combined with domain-specific terminology. As such, they contain free owing unstructured text. Given the usefulness of data extraction from unstructured literature, we aim to show how this can be achieved for the discipline of chemistry. The highly formulaic style of writing most chemists adopt make their contributions well suited to high-throughput Natural Language Processing (NLP) approaches. We have developed the ChemicalTagger parser as a medium-depth, phrase-based semantic NLP tool for the language of chemical experiments. Tagging is based on a modular architecture and uses a combination of OSCAR, domain-specific regex and English taggers to identify parts-of-speech. The ANTLR grammar is used to structure this into tree-based phrases. Using a metric that allows for overlapping annotations, we achieved machine-annotator agreements of 88.9% for phrase recognition and 91.9% for phrase-type identification (Action names). It is possible parse to chemical experimental text using rule-based techniques in conjunction with a formal grammar parser. ChemicalTagger has been deployed for over 10,000 patents and has identified solvents from their linguistic context with >99.5% precision.
144 citations
TL;DR: This article examined how Chinese speakers employ other types of cues in real-time sentence interpretation, such as word order, noun animacy, object marker ba, passive marker bei, and indefinite marker yi.
144 citations