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 651–675 of 1202 papers

Title	Date	Tasks	Status
SemEval 2019 Shared Task: Cross-lingual Semantic Parsing with UCCA - Call for Participation	May 31, 2018	Semantic ParsingUCCA Parsing	—Unverified
SemEval-2019 Task 1: Cross-lingual Semantic Parsing with UCCA	Mar 6, 2019	Semantic ParsingUCCA Parsing	—Unverified
Semi-Supervised Lexicon Learning for Wide-Coverage Semantic Parsing	Aug 1, 2018	Semantic Parsing	—Unverified
Sentence Rewriting for Semantic Parsing	Jan 10, 2019	FormSemantic Parsing	—Unverified
Sequence-based Structured Prediction for Semantic Parsing	Aug 1, 2016	Machine TranslationPrediction	—Unverified
SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models	Jan 16, 2022	Out-of-Distribution GeneralizationSemantic Parsing	—Unverified
ShrdLite: Semantic Parsing Using a Handmade Grammar	Aug 1, 2014	Semantic Parsing	—Unverified
Simple and Effective Text Simplification Using Semantic and Neural Methods	Oct 11, 2018	Machine TranslationSemantic Parsing	—Unverified
Simple, Fast Semantic Parsing with a Tensor Kernel	Jul 2, 2015	Semantic Parsing	—Unverified
Single Classifier Approach for Verb Sense Disambiguation based on Generalized Features	May 1, 2014	Semantic ParsingWord Sense Disambiguation	—Unverified
Skill-Based Few-Shot Selection for In-Context Learning	May 23, 2023	In-Context LearningSemantic Parsing	—Unverified
Software Requirements: A new Domain for Semantic Parsers	Jun 1, 2014	Semantic Parsing	—Unverified
SPADE: Evaluation Dataset for Monolingual Phrase Alignment	May 1, 2018	Machine TranslationParaphrase Identification	—Unverified
SPAGHETTI: Open-Domain Question Answering from Heterogeneous Data Sources with Retrieval and Semantic Parsing	Jun 1, 2024	Open-Domain Question AnsweringQuestion Answering	—Unverified
Span-based Hierarchical Semantic Parsing for Task-Oriented Dialog	Nov 1, 2019	DecoderSemantic Parsing	—Unverified
Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing	Apr 15, 2021	Cross-Lingual TransferDecoder	—Unverified
SPARQL query generation for complex question answering with BERT and BiLSTM-based model	Jun 17, 2020	Knowledge Base Question AnsweringQuestion Answering	—Unverified
Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback	May 5, 2020	FormSemantic Parsing	—Unverified
Splitting compounds with ngrams	Dec 1, 2016	Language ModelingLanguage Modelling	—Unverified
State-of-the-Art Kernels for Natural Language Processing	Jul 1, 2012	Information RetrievalSemantic Parsing	—Unverified
Statistical Models for Frame-Semantic Parsing	Jun 1, 2014	Semantic ParsingSemantic Role Labeling	—Unverified
STOP: A dataset for Spoken Task Oriented Semantic Parsing	Jun 29, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Structural generalization in COGS: Supertagging is (almost) all you need	Oct 21, 2023	AllSemantic Parsing	—Unverified
Structural Transfer Learning in NL-to-Bash Semantic Parsers	Jul 31, 2023	Machine TranslationSemantic Parsing	—Unverified
Structured Case-based Reasoning for Inference-time Adaptation of Text-to-SQL parsers	Jan 10, 2023	DecoderSemantic 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