About

Semantic Parsing is the task of transducing natural language utterances into formal meaning representations. The target meaning representations can be defined according to a wide variety of formalisms. This include linguistically-motivated semantic representations that are designed to capture the meaning of any sentence such as λ-calculus or the abstract meaning representations. Alternatively, for more task-driven approaches to Semantic Parsing, it is common for meaning representations to represent executable programs such as SQL queries, robotic commands, smart phone instructions, and even general-purpose programming languages like Python and Java.

Source: Tranx: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation

Benchmarks

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Subtasks

Datasets

Greatest papers with code

TAPAS: Weakly Supervised Table Parsing via Pre-training

ACL 2020 huggingface/transformers

In this paper, we present TAPAS, an approach to question answering over tables without generating logical forms.

QUESTION ANSWERING SEMANTIC PARSING TRANSFER LEARNING

Learning to Generalize from Sparse and Underspecified Rewards

19 Feb 2019google-research/google-research

The parameters of the auxiliary reward function are optimized with respect to the validation performance of a trained policy.

SEMANTIC PARSING

SLING: A framework for frame semantic parsing

19 Oct 2017google/sling

We describe SLING, a framework for parsing natural language into semantic frames.

SEMANTIC PARSING

Macro Grammars and Holistic Triggering for Efficient Semantic Parsing

EMNLP 2017 percyliang/sempre

To learn a semantic parser from denotations, a learning algorithm must search over a combinatorially large space of logical forms for ones consistent with the annotated denotations.

SEMANTIC PARSING SENTENCE SIMILARITY

Compositional Semantic Parsing on Semi-Structured Tables

IJCNLP 2015 percyliang/sempre

Two important aspects of semantic parsing for question answering are the breadth of the knowledge source and the depth of logical compositionality.

QUESTION ANSWERING SEMANTIC PARSING

A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization

4 Feb 2019naver/sqlova

We present SQLova, the first Natural-language-to-SQL (NL2SQL) model to achieve human performance in WikiSQL dataset.

SEMANTIC PARSING

TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data

ACL 2020 facebookresearch/tabert

Recent years have witnessed the burgeoning of pretrained language models (LMs) for text-based natural language (NL) understanding tasks.

SEMANTIC PARSING TEXT-TO-SQL