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

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Showing 176–200 of 1202 papers

Title	Date	Tasks	Status
A Multimodal LDA Model integrating Textual, Cognitive and Visual Modalities	Oct 1, 2013	Semantic Parsing	—Unverified
Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Prompting	Aug 1, 2023	Domain GeneralizationLanguage Modelling	—Unverified
A Multi-layer LSTM-based Approach for Robot Command Interaction Modeling	Nov 13, 2018	Natural Language UnderstandingSemantic Parsing	—Unverified
Update Frequently, Update Fast: Retraining Semantic Parsing Systems in a Fraction of Time	Oct 15, 2020	Continual LearningGoal-Oriented Dialogue Systems	—Unverified
Conversational Semantic Parsing	Sep 28, 2020	dialog state trackingSemantic Parsing	—Unverified
A Survey on Table Question Answering: Recent Advances	Jul 12, 2022	Question AnsweringSemantic Parsing	—Unverified
A Survey on Semantic Parsing from the perspective of Compositionality	Sep 29, 2020	Knowledge Base Question AnsweringQuestion Answering	—Unverified
A Survey on Semantic Parsing	Dec 3, 2018	Program SynthesisSemantic Parsing	—Unverified
AdaNSP: Uncertainty-driven Adaptive Decoding in Neural Semantic Parsing	Jul 1, 2019	DecoderSemantic Parsing	—Unverified
3D Semantic Parsing of Large-Scale Indoor Spaces	Jun 1, 2016	Semantic Parsing	—Unverified
Copenhagen-Malm\"o: Tree Approximations of Semantic Parsing Problems	Aug 1, 2014	Semantic ParsingSemantic Role Labeling	—Unverified
A Survey on Complex Question Answering over Knowledge Base: Recent Advances and Challenges	Jul 26, 2020	Information RetrievalQuestion Answering	—Unverified
A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions	May 25, 2021	Information RetrievalKnowledge Base Question Answering	—Unverified
A Methodology for Creating Question Answering Corpora Using Inverse Data Annotation	Apr 16, 2020	Question AnsweringSemantic Parsing	—Unverified
A Survey of Syntactic-Semantic Parsing Based on Constituent and Dependency Structures	Jun 19, 2020	Dependency ParsingSemantic 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
A Supervised Semantic Parsing with Lexicon Extension and Syntactic Constraint	Sep 1, 2015	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
A Study of using Syntactic and Semantic Structures for Concept Segmentation and Labeling	Aug 1, 2014	Semantic ParsingSpoken Language Understanding	—Unverified
A Strong Lexical Matching Method for the Machine Comprehension Test	Sep 1, 2015	Common Sense ReasoningCoreference Resolution	—Unverified
Aligning Formal Meaning Representations with Surface Strings for Wide-Coverage Text Generation	Aug 1, 2013	Semantic ParsingText Generation	—Unverified
Active learning for deep semantic parsing	Jul 1, 2018	Active LearningSemantic Parsing	—Unverified

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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