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 951–975 of 1202 papers

Title	Date	Tasks	Status	Hype
Neural Enquirer: Learning to Query Tables in Natural Language	Jun 1, 2016	Learning to ExecuteQuestion Answering	—Unverified	0
Deterministic natural language generation from meaning representations for machine translation	Jun 1, 2016	Machine TranslationSemantic Parsing	—Unverified	0
Cross-Lingual Question Answering Using Common Semantic Space	Jun 1, 2016	Cross-Lingual Question AnsweringEntity Linking	—Unverified	0
The Meaning Factory at SemEval-2016 Task 8: Producing AMRs with Boxer	Jun 1, 2016	Semantic Parsing	—Unverified	0
UCL+Sheffield at SemEval-2016 Task 8: Imitation learning for AMR parsing with an alpha-bound	Jun 1, 2016	AMR ParsingImitation Learning	—Unverified	0
IHS-RD-Belarus at SemEval-2016 Task 9: Transition-based Chinese Semantic Dependency Parsing with Online Reordering and Bootstrapping.	Jun 1, 2016	Dependency ParsingSemantic Dependency Parsing	—Unverified	0
WHUNlp at SemEval-2016 Task DiMSUM: A Pilot Study in Detecting Minimal Semantic Units and their Meanings using Supervised Models	Jun 1, 2016	Feature EngineeringMachine Translation	—Unverified	0
Question Answering over Knowledge Base using Factual Memory Networks	Jun 1, 2016	Information RetrievalKnowledge Base Question Answering	—Unverified	0
Supertagging With LSTMs	Jun 1, 2016	CCG SupertaggingPart-Of-Speech Tagging	—Unverified	0
A Corpus and Semantic Parser for Multilingual Natural Language Querying of OpenStreetMap	Jun 1, 2016	Machine TranslationSemantic Parsing	—Unverified	0
Probabilistic Models for Learning a Semantic Parser Lexicon	Jun 1, 2016	Semantic Parsing	—Unverified	0
Scalable Statistical Relational Learning for NLP	Jun 1, 2016	Coreference ResolutionRelational Reasoning	—Unverified	0
More than Word Cooccurrence: Exploring Support and Opposition in International Climate Negotiations with Semantic Parsing	May 1, 2016	Entity LinkingKeyphrase Extraction	—Unverified	0
Towards Comparability of Linguistic Graph Banks for Semantic Parsing	May 1, 2016	Dependency ParsingSemantic Dependency Parsing	—Unverified	0
Construction of an English Dependency Corpus incorporating Compound Function Words	May 1, 2016	Constituency ParsingDependency Parsing	—Unverified	0
Enhancing The RATP-DECODA Corpus With Linguistic Annotations For Performing A Large Range Of NLP Tasks	May 1, 2016	Semantic Parsing	—Unverified	0
Web Chat Conversations from Contact Centers: a Descriptive Study	May 1, 2016	DescriptiveSemantic Parsing	—Unverified	0
Learning Executable Semantic Parsers for Natural Language Understanding	Mar 22, 2016	Natural Language UnderstandingQuestion Answering	—Unverified	0
Question Answering on Freebase via Relation Extraction and Textual Evidence	Mar 3, 2016	Question AnsweringRelation	CodeCode Available	0
Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing	Jan 22, 2016	Open-Domain Question AnsweringParaphrase Generation	—Unverified	0
Language to Logical Form with Neural Attention	Jan 6, 2016	DecoderForm	CodeCode Available	1
Joint learning of ontology and semantic parser from text	Jan 5, 2016	Semantic Parsing	—Unverified	0
Transforming Dependency Structures to Logical Forms for Semantic Parsing	Jan 1, 2016	Question AnsweringSemantic Parsing	CodeCode Available	0
Learning to Make Inferences in a Semantic Parsing Task	Jan 1, 2016	Machine TranslationNatural Language Inference	—Unverified	0
Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text	Dec 4, 2015	Semantic ParsingSentence	CodeCode Available	0

Show:10 25 50

← PrevPage 39 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