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 501–525 of 1202 papers

Title	Date	Tasks	Status
Improving Company Valuations with Automated Knowledge Discovery, Extraction and Fusion	Oct 19, 2020	Semantic Parsing	—Unverified
A survey of cross-lingual features for zero-shot cross-lingual semantic parsing	Aug 27, 2019	Cross-Lingual Word EmbeddingsSemantic Parsing	—Unverified
Alto: Rapid Prototyping for Parsing and Translation	Apr 1, 2017	Machine TranslationSemantic Parsing	—Unverified
Active Learning for Multilingual Semantic Parser	Jan 30, 2023	Active LearningSemantic Parsing	—Unverified
Improving Generalization in Semantic Parsing by Increasing Natural Language Variation	Feb 13, 2024	Data AugmentationSemantic Parsing	—Unverified
Improving machine translation by training against an automatic semantic frame based evaluation metric	Aug 1, 2013	Machine TranslationSemantic Parsing	—Unverified
PMB5: Gaining More Insight into Neural Semantic Parsing with Challenging Benchmarks	Apr 12, 2024	Semantic ParsingText Generation	—Unverified
Constructing Large Proposition Databases	May 1, 2012	Dependency ParsingMachine Translation	—Unverified
Fully Automatic Semantic MT Evaluation	Jun 1, 2012	Machine TranslationSemantic Parsing	—Unverified
Improving Semantic Parsing for Task Oriented Dialog	Feb 15, 2019	Language ModelingLanguage Modelling	—Unverified
Constrained Semantic Forests for Improved Discriminative Semantic Parsing	Jul 1, 2015	Machine TranslationSemantic Parsing	—Unverified
A Supervised Semantic Parsing with Lexicon Extension and Syntactic Constraint	Sep 1, 2015	Semantic Parsing	—Unverified
From Treebank Parses to Episodic Logic and Commonsense Inference	Jun 1, 2014	Semantic Parsing	—Unverified
From Paraphrasing to Semantic Parsing: Unsupervised Semantic Parsing via Synchronous Semantic Decoding	Jun 11, 2021	FormSemantic Parsing	—Unverified
From Natural Language Instructions to Complex Processes: Issues in Chaining Trigger Action Rules	Jan 8, 2020	Semantic Parsing	—Unverified
A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge	May 2, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Alpage: Transition-based Semantic Graph Parsing with Syntactic Features	Aug 1, 2014	Dependency ParsingSemantic Parsing	—Unverified
From Entity Linking to Question Answering -- Recent Progress on Semantic Grounding Tasks	Dec 1, 2016	document understandingEntity Linking	—Unverified
Computational linking theory	Oct 8, 2016	Semantic ParsingSemantic Role Labeling	—Unverified
Freebase QA: Information Extraction or Semantic Parsing?	Jun 1, 2014	Open Information ExtractionQuestion Answering	—Unverified
Compressing Transformer-Based Semantic Parsing Models using Compositional Code Embeddings	Oct 10, 2020	Semantic Parsing	—Unverified
A Study of using Syntactic and Semantic Structures for Concept Segmentation and Labeling	Aug 1, 2014	Semantic ParsingSpoken Language Understanding	—Unverified
Framework of Semantic Role Assignment based on Extended Lexical Conceptual Structure: Comparison with VerbNet and FrameNet	Apr 1, 2012	Semantic ParsingSemantic Role Labeling	—Unverified
Frame Semantics across Languages: Towards a Multilingual FrameNet	Aug 1, 2018	Question AnsweringSemantic Parsing	—Unverified
Frame-Semantic Role Labeling with Heterogeneous Annotations	Jul 1, 2015	Domain AdaptationSemantic Parsing	—Unverified

Show:10 25 50

← PrevPage 21 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