Year: 2016
Type: conference-paper
Abstract: Recent years have seen a dramatic increase in interest in semanticallyinformed natural language processing, including parsing into semantic representations, grounded language processing that connects linguistic structures to world representations, proposals to integrate compositional and distributional approaches to semantics, and approaches to semanticallysensitive tasks including sentiment analysis, summarization, generation, machine translation, and information extraction which take into account linguistic structure beyond ngrams.The semantic inputs to this work include a wide range of representations, from word embeddings, to syntactic dependencies used as a proxy for semantic dependencies, to sentencelevel semantic representations either partial (e.g.semantic role labels) or fully articulated.lexical representation, the syntaxsemantics interface, methodology for evaluation of semantically precise grammars, and practical applications of 'deep' processing.Applied and industrial experience includes cofounding the software company YY Technologies, which from 20002002 sold automated consumer email response technology incorporating the ERG; and since 2009 developing online educational software using the ERG for teaching English writing skills, first as part of the Education Program for Gifted Youth (EPGY) at Stanford, and for the past three years as a senior researcher at the EPGY spinoff company Redbird Advanced Learning, based in Oakland, California.
DOI: 10.18653/v1/n16-4001
Institution: University of Washington
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W2471243283