Logical Forms

The paper describes a principled approach to the problem of deriving database queries from logical forms produced by a general NL in- terface. Our method attempts to construct a database …...

AbstractIn this paper we present an overview of an approach developed at Microsoft Research to generate strings for named entities such as places and dates. This approach uses abstract representations …...

We present an approach to training a joint syntactic and semantic parser that com- bines syntactic training information from CCGbank with semantic training informa- tion from a knowledge base via …...

A core problem in learning semantic parsers from denotations is picking out consistent logical forms—those that yield the correct denotation—from a combina- torially large space. To control the search space, …...

Semantic parsing aims at mapping nat- ural language to machine interpretable meaning representations. Traditional ap- proaches rely on high-quality lexicons, manually-built templates, and linguis- tic features which are either domain- …...

We present a semi-automated framework for constructing factoid question answering (QA) datasets, where an array of question character- istics are formalized, including structure com- plexity, function, commonness, answer cardi- nality, …...

We present a novel semi-supervised approach for sequence transduction and apply it to se- mantic parsing. The unsupervised component is based on a generative model in which latent sentences generate …...

We consider the task of learning a context- dependent mapping from utterances to de- notations. With only denotations at train- ing time, we must search over a combina- torially large …...

AbstractWe have been developing an end-to-end math problem solving system that accepts natural language input. The current paper focuses on how we analyze the problem sentences to produce logical forms. …...

AbstractA major hurdle on the road to conversational interfaces is the difficulty in collecting data that maps language utterances to logical forms. One prominent approach for data collection has been …...

AbstractMeaning representation is an important component of semantic parsing. Although researchers have designed a lot of meaning representations, recent work focuses on only a few of them. Thus, the impact …...

AbstractPrevious studies on Natural Language Generation (NLG) from structured data have primarily focused on surface-level descriptions of record sequences. However, for complex structured data, e.g., multi-row tables, it is often …...

AbstractSemantic parsing maps natural language (NL) utterances into logical forms (LFs), which underpins many advanced NLP problems. Semantic parsers gain performance boosts with deep neural networks, but inherit vulnerabilities against …...

AbstractQuestion answering over knowledge bases (KBQA) for complex questions is a challenging task in natural language processing. Recently, generation-based methods that translate natural language questions to executable logical forms have …...

AbstractGenerative question answering (QA) models generate answers to questions either solely based on the parameters of the model (the closed-book setting) or additionally retrieving relevant evidence (the open-book setting). Generative …...