Events Calendar

NL Seminar: Semantic Parsing as Machine Translation

Speaker: Jonathan May, USC/ISI

Talk Title: Semantic Parsing as Machine Translation

Series: Natural Language Seminar

Abstract: We cast the generation of semantic graphs from natural language text as a machine translation problem, where the source language is English and the target language is a labeled graph representing a semantic interpretation, known as an Abstract Meaning Representation (AMR). Via a series of data transformations we create a training set that is amenable to a string-to-tree syntax mt decoder. Previous work in SBMT and AMR parsing is combined to yield a trainable system that achieves state-of-the-art parsing results.


Biography: Jonathan May is a computer scientist at USC-ISI, where he also received a PhD in 2010. His current focus areas are in machine translation, machine learning, and natural language understanding. Jonathan co-developed and patented a highly portable method for optimizing thousands of features in machine translation systems that has since been incorporated into all leading open source MT systems. He has previously worked in automata theory and information extraction and at SDL Language Weaver and BBN Technologies.

Host: Nima Pourdamghani and Kevin Knight

More Info: http://nlg.isi.edu/nl-seminar/

Location: Information Science Institute (ISI) - 6th Flr Conf Rm # 689, Marina Del Rey

Audiences: Everyone Is Invited

Contact: Peter Zamar

Event Link: http://nlg.isi.edu/nl-seminar/