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A Survey on Semantic Parsing

2 Pith papers cite this work. Polarity classification is still indexing.

2 Pith papers citing it
abstract

A significant amount of information in today's world is stored in structured and semi-structured knowledge bases. Efficient and simple methods to query them are essential and must not be restricted to only those who have expertise in formal query languages. The field of semantic parsing deals with converting natural language utterances to logical forms that can be easily executed on a knowledge base. In this survey, we examine the various components of a semantic parsing system and discuss prominent work ranging from the initial rule based methods to the current neural approaches to program synthesis. We also discuss methods that operate using varying levels of supervision and highlight the key challenges involved in the learning of such systems.

fields

cs.CL 2

years

2026 1 2019 1

verdicts

UNVERDICTED 2

representative citing papers

Semantically Driven Auto-completion

cs.CL · 2019-06-22 · unverdicted · novelty 4.0

Semantically guided auto-completion for natural language query formulation in financial analytics platforms.

citing papers explorer

Showing 2 of 2 citing papers.

  • A Pilot Benchmark for NL-to-FOL Translation in Planetary Exploration cs.CL · 2026-05-18 · unverdicted · none · ref 4 · internal anchor

    The authors create and release a new annotated benchmark for natural language to first-order logic translation using historical NASA planetary mission documentation from 2003-2013.

  • Semantically Driven Auto-completion cs.CL · 2019-06-22 · unverdicted · none · ref 27 · internal anchor

    Semantically guided auto-completion for natural language query formulation in financial analytics platforms.