Time+Place: Sunday 21/12/2014 14:30 Room 337-8 Taub Bld.
Title: Scalable algorithms for translating natural language to logical form
Speaker: Jonathan Berant - CS-Lecture http://nlp.stanford.edu/joberant/
Affiliation: Stanford-Dept. of Computer Science
Host: Alon Itai


Conversational interfaces and virtual assistants such as Apple's Siri, 
Google Now, and Facebook Graph Search, have led to a rising interest in 
systems that can translate natural language commands and questions to 
formal logical forms (like SQL queries) that can be executed against a 
knowledge base.  A major challenge has been to scale these systems, 
known as semantic parsers, to large knowledge bases. In this talk, 
I will describe novel algorithms for large scale semantic parsing.

A fundamental characteristic of semantic parsing against large knowledge 
bases is that the space of possible logical forms grows quickly with the 
length of the input sentence. Our first algorithm learns to efficiently 
search through this space by explicitly scoring partial logical forms, 
combining ideas from agenda-based parsing and reinforcement learning. 
Compared to previous methods, our parser is almost an order of magnitude 
faster, while maintaining state-of-the-art accuracy.  The second algorithm 
addresses the problem of language variability, that is, the fact that the 
same logical form can be expressed in a myriad of ways in natural language.  
We learn to paraphrase an input question ("Where is Obama from?") to a 
canonical form ("What is the place of birth of Barack Obama?") that can be 
easily mapped to a logical form.  This allows us to exploit the large amounts 
of free text that are available on the web, leading to a state-of-the-art 
semantic parser that scales to a knowledge base containing hundreds of millions 
of facts.

This is joint work with Percy Liang.

Short Bio:

Jonathan Berant is a post-doctoral fellow at Stanford's Department of
Computer Science, and a member of The Stanford Natural Language 
Processing Group.  He earned his B.Sc in computer science and linguistics, 
and Ph.D in computer science from Tel-Aviv University. Jonathan was an Azrieli 
fellow and an IBM fellow during his graduate studies, and a Rothschild fellow 
during his post-doctoral period.  His work has been recognized by a best paper 
award in EMNLP 2014, a best student paper award in ACL 2011, and another two 
best paper nominations.