Semantic Parsing

195 papers with code • 17 benchmarks • 32 datasets

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

Greatest papers with code

TAPAS: Weakly Supervised Table Parsing via Pre-training

huggingface/transformers ACL 2020

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

Question Answering Semantic Parsing +1

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

huggingface/transformers arXiv 2019

Transfer learning, where a model is first pre-trained on a data-rich task before being fine-tuned on a downstream task, has emerged as a powerful technique in natural language processing (NLP).

Common Sense Reasoning Question Answering +3

Learning to Generalize from Sparse and Underspecified Rewards

google-research/google-research 19 Feb 2019

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

Semantic Parsing

Non-Autoregressive Semantic Parsing for Compositional Task-Oriented Dialog

facebookresearch/pytext NAACL 2021

Semantic parsing using sequence-to-sequence models allows parsing of deeper representations compared to traditional word tagging based models.

Semantic Parsing

N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models

HIT-SCIR/ltp 24 Sep 2020

In addition, knowledge distillation where the single-task model teaches the multi-task model is further introduced to encourage the multi-task model to surpass its single-task teacher.

Chinese Word Segmentation Dependency Parsing +7

The Natural Language Decathlon: Multitask Learning as Question Answering

salesforce/decaNLP ICLR 2019

Though designed for decaNLP, MQAN also achieves state of the art results on the WikiSQL semantic parsing task in the single-task setting.

Domain Adaptation Machine Translation +9

SLING: A framework for frame semantic parsing

google/sling 19 Oct 2017

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

Semantic Parsing

RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers

PaddlePaddle/PaddleNLP ACL 2020

The generalization challenge lies in (a) encoding the database relations in an accessible way for the semantic parser, and (b) modeling alignment between database columns and their mentions in a given query.

Semantic Parsing Text-To-Sql