Weakly-supervised Semantic Parsing with Abstract Examples

11/14/2017
by   Omer Goldman, et al.
0

Semantic parsers translate language utterances to programs, but are often trained from utterance-denotation pairs only. Consequently, parsers must overcome the problem of spuriousness at training time, where an incorrect program found at search time accidentally leads to a correct denotation. We propose that in small well-typed domains, we can semi-automatically generate an abstract representation for examples that facilitates information sharing across examples. This alleviates spuriousness, as the probability of randomly obtaining a correct answer from a program decreases across multiple examples. We test our approach on CNLVR, a challenging visual reasoning dataset, where spuriousness is central because denotations are either TRUE or FALSE, and thus random programs have high probability of leading to a correct denotation. We develop the first semantic parser for this task and reach 83.5 15.7 far.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/09/2019

Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs

Semantic parsing aims to map natural language utterances onto machine in...
research
04/25/2017

From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood

Our goal is to learn a semantic parser that maps natural language uttera...
research
07/13/2021

Enforcing Consistency in Weakly Supervised Semantic Parsing

The predominant challenge in weakly supervised semantic parsing is that ...
research
06/12/2019

Unified Semantic Parsing with Weak Supervision

Semantic parsing over multiple knowledge bases enables a parser to explo...
research
04/12/2021

Learning from Executions for Semantic Parsing

Semantic parsing aims at translating natural language (NL) utterances on...
research
05/28/2022

Learning from Self-Sampled Correct and Partially-Correct Programs

Program synthesis aims to generate executable programs that are consiste...
research
01/30/2019

Effective weakly supervised semantic frame induction using expression sharing in hierarchical hidden Markov models

We present a framework for the induction of semantic frames from utteran...

Please sign up or login with your details

Forgot password? Click here to reset