200 citations · 811 across the 66 of their papers we have counts for
6 papers · 1 filter
Learning an Executable Neural Semantic Parser
Jianpeng Cheng, Siva Reddy, Vijay Saraswat +1
This paper describes a neural semantic parser that maps natural language utterances onto logical forms which can be executed against a task-specific environment, such as a knowledg…
Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks
Rajarshi Das, Manzil Zaheer, Siva Reddy +1
Existing question answering methods infer answers either from a knowledge base or from raw text. While knowledge base (KB) methods are good at answering compositional questions, th…
Learning Structured Natural Language Representations for Semantic Parsing
Jianpeng Cheng, Siva Reddy, Vijay Saraswat +1
We introduce a neural semantic parser that converts natural language utterances to intermediate representations in the form of predicate-argument structures, which are induced with…
Universal Dependencies to Logical Forms with Negation Scope
Federico Fancellu, Siva Reddy, Adam Lopez +1
Many language technology applications would benefit from the ability to represent negation and its scope on top of widely-used linguistic resources. In this paper, we investigate t…
Universal Semantic Parsing
Siva Reddy, Oscar Täckström, Slav Petrov +2
Universal Dependencies (UD) offer a uniform cross-lingual syntactic representation, with the aim of advancing multilingual applications. Recent work shows that semantic parsing can…
Predicting Target Language CCG Supertags Improves Neural Machine Translation
Maria Nadejde, Siva Reddy, Rico Sennrich +4
Neural machine translation (NMT) models are able to partially learn syntactic information from sequential lexical information. Still, some complex syntactic phenomena such as prepo…