Semantic Parsing

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

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 976–1000 of 1202 papers

Title	Date	Tasks	Status
Dataset and Enhanced Model for Eligibility Criteria-to-SQL Semantic Parsing	May 1, 2020	DiversitySemantic Parsing	—Unverified
Data Synthesis and Iterative Refinement for Neural Semantic Parsing without Annotated Logical Forms	Oct 1, 2022	DenoisingLanguage Modeling	—Unverified
DBRouting: Routing End User Queries to Databases for Answerability	Jan 27, 2025	Logical ReasoningSemantic Parsing	—Unverified
Debugging Frame Semantic Role Labeling	Jan 22, 2019	Semantic ParsingSemantic Role Labeling	—Unverified
Decoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQL	Jun 4, 2021	Semantic ParsingSQL Parsing	—Unverified
DeepCx: A transition-based approach for shallow semantic parsing with complex constructional triggers	Oct 1, 2018	Semantic Parsing	—Unverified
Deeper syntax for better semantic parsing	Dec 1, 2016	Semantic ParsingSemantic Role Labeling	—Unverified
Deep Learning and Continuous Representations for Natural Language Processing	May 1, 2015	Deep LearningInformation Retrieval	—Unverified
Deep Learning on Graphs for Natural Language Processing	Jun 1, 2021	Deep Learninggraph construction	—Unverified
Deep Neural Network applied to Part-of-Speech Tagging (R\'eseau de neurones profond pour l'\'etiquetage morpho-syntaxique) [in French]	Jul 1, 2014	Part-Of-Speech TaggingSemantic Parsing	—Unverified
Deep Neural Solver for Math Word Problems	Sep 1, 2017	Feature EngineeringMachine Translation	—Unverified
Deep Portrait Delighting	Mar 22, 2022	Semantic ParsingSensitivity	—Unverified
Deep Semantic Parsing of Freehand Sketches with Homogeneous Transformation, Soft-Weighted Loss, and Staged Learning	Oct 14, 2019	Domain AdaptationImage Retrieval	—Unverified
Delexicalized transfer parsing for low-resource languages using transformed and combined treebanks	Aug 1, 2017	Cross-Lingual TransferDependency Parsing	—Unverified
Dependency-based Hybrid Trees for Semantic Parsing	Sep 1, 2018	Semantic Parsing	—Unverified
Depressive, Drug Abusive, or Informative: Knowledge-aware Study of News Exposure during COVID-19 Outbreak	Jul 30, 2020	ArticlesInformativeness	—Unverified
Detailed Garment Recovery from a Single-View Image	Aug 3, 2016	parameter estimationSemantic Parsing	—Unverified
Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing	Nov 1, 2021	Out of Distribution (OOD) DetectionSemantic Parsing	—Unverified
Detecting novel metaphor using selectional preference information	Jun 1, 2016	Semantic ParsingSentiment Analysis	—Unverified
Deterministic natural language generation from meaning representations for machine translation	Jun 1, 2016	Machine TranslationSemantic Parsing	—Unverified
Developing Production-Level Conversational Interfaces with Shallow Semantic Parsing	Nov 1, 2018	Dialogue ManagementGeneral Classification	—Unverified
Development of a General-Purpose Categorial Grammar Treebank	May 1, 2020	Semantic Parsing	—Unverified
DEXTER: Deep Encoding of External Knowledge for Named Entity Recognition in Virtual Assistants	Aug 15, 2021	named-entity-recognitionNamed Entity Recognition	—Unverified
Diagnosing Transformers in Task-Oriented Semantic Parsing	May 27, 2021	Semantic Parsingvalid	—Unverified
Dialog2API: Task-Oriented Dialogue with API Description and Example Programs	Dec 20, 2022	In-Context LearningSemantic Parsing	—Unverified

Show:10 25 50

← PrevPage 40 of 49Next →

All datasets WikiTableQuestions spider CFQ WebQuestionsSP WikiSQL ATIS Geo PTG (czech, MRP 2020)AMR (chinese, MRP 2020)AMR (english, MRP 2020)DRG (english, MRP 2020)DRG (german, MRP 2020)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ARTEMIS-DA	Accuracy (Test)	80.8	—	Unverified
2	SynTQA (Oracle)	Test Accuracy	77.5	—	Unverified
3	TabLaP	Accuracy (Test)	76.6	—	Unverified
4	SynTQA (GPT)	Accuracy (Test)	74.4	—	Unverified
5	Mix SC	Accuracy (Test)	73.6	—	Unverified
6	SynTQA (RF)	Accuracy (Test)	71.6	—	Unverified
7	CABINET	Accuracy (Test)	69.1	—	Unverified
8	NormTab+TabSQLify	Accuracy (Test)	68.63	—	Unverified
9	Chain-of-Table	Accuracy (Test)	67.31	—	Unverified
10	Tab-PoT	Accuracy (Test)	66.78	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RESDSQL-3B + NatSQL	Accuracy	84.1	—	Unverified
2	code-davinci-002 175B (LEVER)	Accuracy	81.9	—	Unverified
3	RASAT+PICARD	Accuracy	75.5	—	Unverified
4	Graphix-3B + PICARD	Accuracy	74	—	Unverified
5	T5-3B + PICARD	Accuracy	71.9	—	Unverified
6	SADGA + GAP	Accuracy	70.1	—	Unverified
7	RATSQL + GAP	Accuracy	69.7	—	Unverified
8	RATSQL + Grammar-Augmented Pre-Training	Accuracy	69.6	—	Unverified
9	RATSQL + BERT	Accuracy	65.6	—	Unverified
10	Exact Set Matching	Accuracy	19.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Dynamic Least-to-Most Prompting	Exact Match	95	—	Unverified
2	LeAR	Exact Match	90.9	—	Unverified
3	T5-3B w/ Intermediate Representations	Exact Match	83.8	—	Unverified
4	Hierarchical Poset Decoding	Exact Match	69	—	Unverified
5	Universal Transformer	Exact Match	18.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ReaRev	Accuracy	76.4	—	Unverified
2	NSM+h	Accuracy	74.3	—	Unverified
3	CBR-KBQA	Accuracy	70	—	Unverified
4	STAGG (Yih et al., 2016)	Accuracy	63.9	—	Unverified
5	T5-11B (Raffel et al., 2020)	Accuracy	56.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CABINET	Denotation accuracy (test)	89.5	—	Unverified
2	TAPEX-Large (weak supervision)	Denotation accuracy (test)	89.5	—	Unverified
3	ReasTAP-Large (weak supervision)	Denotation accuracy (test)	89.2	—	Unverified
4	NL2SQL-BERT	Accuracy	89	—	Unverified
5	TAPAS-Large (weak supervision)	Denotation accuracy (test)	83.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PhraseTransformer	Accuracy	90.4	—	Unverified
2	Tranx	Accuracy	86.2	—	Unverified
3	ASN (Rabinovich et al., 2017)	Accuracy	85.3	—	Unverified
4	ZH15 (Zhao and Huang, 2015)	Accuracy	84.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	coarse2fine	Accuracy	88.2	—	Unverified
2	PhraseTransformer	Accuracy	87.9	—	Unverified
3	Tranx	Accuracy	87.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN + RobeCzech	F1	92.36	—	Unverified
2	PERIN	F1	92.24	—	Unverified
3	HUJI-KU	F1	58	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN	F1	80.52	—	Unverified
2	HUJI-KU	F1	45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN	F1	80.23	—	Unverified
2	HUJI-KU	F1	52	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN	F1	94.16	—	Unverified
2	HUJI-KU	F1	63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN	F1	89.83	—	Unverified
2	HUJI-KU	F1	62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN	F1	92.73	—	Unverified
2	HUJI-KU	F1	80	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN	F1	89.19	—	Unverified
2	HUJI-KU	F1	54	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TAPEX-Large	Denotation Accuracy	74.5	—	Unverified
2	TAPAS-Large	Accuracy	67.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN	F1	76.4	—	Unverified
2	HUJI-KU	F1	73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PERIN	F1	81.01	—	Unverified
2	HUJI-KU	F1	75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HSP	EM	66.18	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ReasonBERTR	F1 Score	41.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MeMCE	Exact	40.3	—	Unverified