SOTAVerified

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

Showing 601650 of 1202 papers

TitleStatusHype
LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network0
Syn-QG: Syntactic and Shallow Semantic Rules for Question Generation0
A Methodology for Creating Question Answering Corpora Using Inverse Data Annotation0
Bootstrapping a Crosslingual Semantic ParserCode0
TAPAS: Weakly Supervised Table Parsing via Pre-trainingCode0
Revisit Systematic Generalization via Meaningful LearningCode0
Exploring Neural Models for Parsing Natural Language into First-Order Logic0
A Data Efficient End-To-End Spoken Language Understanding Architecture0
Compositional Neural Machine Translation by Removing the Lexicon from Syntax0
How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Context0
Don't Parse, Generate! A Sequence to Sequence Architecture for Task-Oriented Semantic Parsing0
From Natural Language Instructions to Complex Processes: Issues in Chaining Trigger Action Rules0
Metagross: Meta Gated Recursive Controller Units for Sequence Modeling0
Measuring Compositional Generalization: A Comprehensive Method on Realistic DataCode0
Fast Intent Classification for Spoken Language UnderstandingCode0
Novel positional encodings to enable tree-based transformersCode0
Merging Weak and Active Supervision for Semantic ParsingCode0
Zero-Shot Semantic Parsing for InstructionsCode0
Data-Free Point Cloud Network for 3D Face Recognition0
Learning from Explanations with Neural Execution TreeCode0
EUSP: An Easy-to-Use Semantic Parsing PlatForm0
Graph Enhanced Cross-Domain Text-to-SQL Generation0
Span-based Hierarchical Semantic Parsing for Task-Oriented Dialog0
BME-UW at SRST-2019: Surface realization with Interpreted Regular Tree Grammars0
\'UFAL-Oslo at MRP 2019: Garage Sale Semantic Parsing0
\'UFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared TaskCode0
LIMIT-BERT : Linguistic Informed Multi-Task BERT0
Positional Attention-based Frame Identification with BERT: A Deep Learning Approach to Target Disambiguation and Semantic Frame Selection0
Multi-Module System for Open Domain Chinese Question Answering over Knowledge Base0
ÚFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared TaskCode0
A Hybrid Semantic Parsing Approach for Tabular Data Analysis0
Universal Decompositional Semantic Parsing0
Question Answering over Knowledge Graphs via Structural Query Patterns0
Diversity in Fashion Recommendation using Semantic ParsingCode0
Content Enhanced BERT-based Text-to-SQL GenerationCode0
Deep Semantic Parsing of Freehand Sketches with Homogeneous Transformation, Soft-Weighted Loss, and Staged Learning0
Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge BaseCode0
Adapting a FrameNet Semantic Parser for Spoken Language Understanding Using Adversarial Learning0
MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging0
Robust Semantic Parsing with Adversarial Learning for Domain Generalization0
Semantic Graph Parsing with Recurrent Neural Network DAG Grammars0
Improving Semantic Parsing with Neural Generator-Reranker Architecture0
A Split-and-Recombine Approach for Follow-up Query AnalysisCode0
CORD: A Consolidated Receipt Dataset for Post-OCR ParsingCode0
Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning0
Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract ProgramsCode0
Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering0
Broad-Coverage Semantic Parsing as Transduction0
A Sketch-Based System for Semantic ParsingCode0
Exploiting Frame-Semantics and Frame-Semantic Parsing for Automatic Extraction of Typological Information from Descriptive Grammars of Natural Languages0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ARTEMIS-DAAccuracy (Test)80.8Unverified
2SynTQA (Oracle)Test Accuracy77.5Unverified
3TabLaPAccuracy (Test)76.6Unverified
4SynTQA (GPT)Accuracy (Test)74.4Unverified
5Mix SCAccuracy (Test)73.6Unverified
6SynTQA (RF)Accuracy (Test)71.6Unverified
7CABINETAccuracy (Test)69.1Unverified
8NormTab+TabSQLifyAccuracy (Test)68.63Unverified
9Chain-of-TableAccuracy (Test)67.31Unverified
10Tab-PoTAccuracy (Test)66.78Unverified
#ModelMetricClaimedVerifiedStatus
1RESDSQL-3B + NatSQLAccuracy84.1Unverified
2code-davinci-002 175B (LEVER)Accuracy81.9Unverified
3RASAT+PICARDAccuracy75.5Unverified
4Graphix-3B + PICARDAccuracy74Unverified
5T5-3B + PICARDAccuracy71.9Unverified
6SADGA + GAPAccuracy70.1Unverified
7RATSQL + GAPAccuracy69.7Unverified
8RATSQL + Grammar-Augmented Pre-TrainingAccuracy69.6Unverified
9RATSQL + BERTAccuracy65.6Unverified
10Exact Set MatchingAccuracy19.7Unverified
#ModelMetricClaimedVerifiedStatus
1Dynamic Least-to-Most PromptingExact Match95Unverified
2LeARExact Match90.9Unverified
3T5-3B w/ Intermediate RepresentationsExact Match83.8Unverified
4Hierarchical Poset DecodingExact Match69Unverified
5Universal TransformerExact Match18.9Unverified
#ModelMetricClaimedVerifiedStatus
1ReaRevAccuracy76.4Unverified
2NSM+hAccuracy74.3Unverified
3CBR-KBQAAccuracy70Unverified
4STAGG (Yih et al., 2016)Accuracy63.9Unverified
5T5-11B (Raffel et al., 2020)Accuracy56.5Unverified
#ModelMetricClaimedVerifiedStatus
1CABINETDenotation accuracy (test)89.5Unverified
2TAPEX-Large (weak supervision)Denotation accuracy (test)89.5Unverified
3ReasTAP-Large (weak supervision)Denotation accuracy (test)89.2Unverified
4NL2SQL-BERTAccuracy89Unverified
5TAPAS-Large (weak supervision)Denotation accuracy (test)83.6Unverified
#ModelMetricClaimedVerifiedStatus
1PhraseTransformerAccuracy90.4Unverified
2TranxAccuracy86.2Unverified
3ASN (Rabinovich et al., 2017)Accuracy85.3Unverified
4ZH15 (Zhao and Huang, 2015)Accuracy84.2Unverified
#ModelMetricClaimedVerifiedStatus
1coarse2fineAccuracy88.2Unverified
2PhraseTransformerAccuracy87.9Unverified
3TranxAccuracy87.7Unverified
#ModelMetricClaimedVerifiedStatus
1PERIN + RobeCzechF192.36Unverified
2PERINF192.24Unverified
3HUJI-KUF158Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF180.52Unverified
2HUJI-KUF145Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF180.23Unverified
2HUJI-KUF152Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF194.16Unverified
2HUJI-KUF163Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF189.83Unverified
2HUJI-KUF162Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF192.73Unverified
2HUJI-KUF180Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF189.19Unverified
2HUJI-KUF154Unverified
#ModelMetricClaimedVerifiedStatus
1TAPEX-LargeDenotation Accuracy74.5Unverified
2TAPAS-LargeAccuracy67.2Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF176.4Unverified
2HUJI-KUF173Unverified
#ModelMetricClaimedVerifiedStatus
1PERINF181.01Unverified
2HUJI-KUF175Unverified
#ModelMetricClaimedVerifiedStatus
1HSPEM66.18Unverified
#ModelMetricClaimedVerifiedStatus
1ReasonBERTRF1 Score41.3Unverified
#ModelMetricClaimedVerifiedStatus
1MeMCEExact40.3Unverified