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 1051–1075 of 1202 papers

Title	Date	Tasks	Status
Exploring Unexplored Generalization Challenges for Cross-Database Semantic Parsing	Jul 1, 2020	Semantic Parsing	—Unverified
Extracting a bilingual semantic grammar from FrameNet-annotated corpora	May 1, 2014	Semantic ParsingText Generation	—Unverified
Extrinsic Evaluation of Machine Translation Metrics	Dec 20, 2022	Dialogue State TrackingMachine Translation	—Unverified
Fast and Accurate Capitalization and Punctuation for Automatic Speech Recognition Using Transformer and Chunk Merging	Aug 7, 2019	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Fast Forward Through Opportunistic Incremental Meaning Representation Construction	Jul 1, 2017	Decision MakingDialogue Understanding	—Unverified
Fast semantic parsing with well-typedness guarantees	Sep 15, 2020	Dependency ParsingSemantic Parsing	—Unverified
FedParsing: a Semi-Supervised Federated Learning Model on Semantic Parsing	Nov 16, 2021	Federated LearningSemantic Parsing	—Unverified
Few-shot Multi-hop Question Answering over Knowledge Base	Dec 14, 2021	Few-Shot LearningKnowledge Base Question Answering	—Unverified
Few-Shot Novel Concept Learning for Semantic Parsing	Nov 1, 2021	Novel ConceptsProgram Synthesis	—Unverified
Few-Shot Semantic Parsing with Language Models Trained On Code	Dec 16, 2021	Semantic Parsing	—Unverified
Few-Shot Semantic Parsing with Language Models Trained On Code	Jan 16, 2022	Semantic Parsing	—Unverified
Filling Memory Gaps: Enhancing Continual Semantic Parsing via SQL Syntax Variance-Guided LLMs without Real Data Replay	Dec 10, 2024	Continual LearningLanguage Modeling	—Unverified
Findings from Experiments of On-line Joint Reinforcement Learning of Semantic Parser and Dialogue Manager with real Users	Oct 25, 2021	Dialogue ManagementManagement	—Unverified
First approach toward Semantic Role Labeling for Basque	May 1, 2014	feature selectionMachine Translation	—Unverified
First steps towards a Predicate Matrix	Jan 1, 2014	Natural Language InferenceQuestion Answering	—Unverified
FLIN: A Flexible Natural Language Interface for Web Navigation	Oct 24, 2020	Semantic Parsingslot-filling	—Unverified
Frame-Semantic Parsing	Mar 1, 2014	Semantic Parsing	—Unverified
Frame-Semantic Role Labeling with Heterogeneous Annotations	Jul 1, 2015	Domain AdaptationSemantic Parsing	—Unverified
Frame Semantics across Languages: Towards a Multilingual FrameNet	Aug 1, 2018	Question AnsweringSemantic Parsing	—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
Freebase QA: Information Extraction or Semantic Parsing?	Jun 1, 2014	Open Information ExtractionQuestion Answering	—Unverified
From Entity Linking to Question Answering -- Recent Progress on Semantic Grounding Tasks	Dec 1, 2016	document understandingEntity Linking	—Unverified
From Natural Language Instructions to Complex Processes: Issues in Chaining Trigger Action Rules	Jan 8, 2020	Semantic Parsing	—Unverified
From Paraphrasing to Semantic Parsing: Unsupervised Semantic Parsing via Synchronous Semantic Decoding	Jun 11, 2021	FormSemantic Parsing	—Unverified
From Treebank Parses to Episodic Logic and Commonsense Inference	Jun 1, 2014	Semantic 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