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 576–600 of 1202 papers

Title	Date	Tasks	Status
Joint Case Argument Identification for Japanese Predicate Argument Structure Analysis	Jul 1, 2015	Semantic ParsingSemantic Role Labeling	—Unverified
Data-Free Point Cloud Network for 3D Face Recognition	Nov 12, 2019	3D Object ClassificationFace Recognition	—Unverified
Large-scale CCG Induction from the Groningen Meaning Bank	Jun 1, 2014	Question AnsweringSemantic Parsing	—Unverified
Large-scale Semantic Parsing via Schema Matching and Lexicon Extension	Aug 1, 2013	Semantic Parsing	—Unverified
Large-scale Semantic Parsing without Question-Answer Pairs	Jan 1, 2014	Graph MatchingSemantic Parsing	—Unverified
Latent Structure Models for Natural Language Processing	Jul 1, 2019	Language ModelingLanguage Modelling	—Unverified
Layers of Interpretation: On Grammar and Compositionality	Apr 1, 2015	Machine TranslationSemantic Parsing	—Unverified
Laziness Is a Virtue When It Comes to Compositionality in Neural Semantic Parsing	May 7, 2023	Semantic ParsingText to SQL	—Unverified
LB-KBQA: Large-language-model and BERT based Knowledge-Based Question and Answering System	Feb 5, 2024	DiversityIntent Recognition	—Unverified
Lean Question Answering over Freebase from Scratch	Jun 1, 2015	ChunkingNamed Entity Recognition (NER)	—Unverified
Learning a Compositional Semantics for Freebase with an Open Predicate Vocabulary	Jan 1, 2015	Coreference ResolutionOpen Information Extraction	—Unverified
Joint A* CCG Parsing and Semantic Role Labelling	Sep 1, 2015	Semantic ParsingSemantic Role Labeling	—Unverified
Learning a Lexicon for Broad-coverage Semantic Parsing	Jun 1, 2014	Semantic Parsing	—Unverified
Detailed Garment Recovery from a Single-View Image	Aug 3, 2016	parameter estimationSemantic Parsing	—Unverified
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing	Jan 1, 2021	Generalization BoundsMachine Translation	—Unverified
Iterative Utterance Segmentation for Neural Semantic Parsing	Dec 13, 2020	SegmentationSemantic Parsing	—Unverified
A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing	Jan 1, 2014	Imitation LearningSemantic Parsing	—Unverified
A Data Efficient End-To-End Spoken Language Understanding Architecture	Feb 14, 2020	ChunkingLanguage Modeling	—Unverified
Learning Cross-lingual Distributed Logical Representations for Semantic Parsing	Jun 14, 2018	Semantic Parsing	—Unverified
Deterministic natural language generation from meaning representations for machine translation	Jun 1, 2016	Machine TranslationSemantic Parsing	—Unverified
Learning Executable Semantic Parsers for Natural Language Understanding	Mar 22, 2016	Natural Language UnderstandingQuestion Answering	—Unverified
Learning to Jointly Predict Ellipsis and Comparison Structures	Aug 1, 2016	Question AnsweringReading Comprehension	—Unverified
Developing Production-Level Conversational Interfaces with Shallow Semantic Parsing	Nov 1, 2018	Dialogue ManagementGeneral Classification	—Unverified
Development of a General-Purpose Categorial Grammar Treebank	May 1, 2020	Semantic Parsing	—Unverified
Learning Web-based Procedures by Reasoning over Explanations and Demonstrations in Context	Jul 1, 2020	Language AcquisitionProgram Synthesis	—Unverified

Show:10 25 50

← PrevPage 24 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