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 801850 of 1202 papers

TitleStatusHype
Confidence Modeling for Neural Semantic ParsingCode0
Improving a Neural Semantic Parser by Counterfactual Learning from Human Bandit FeedbackCode0
World Knowledge for Abstract Meaning Representation Parsing0
Integrating Generative Lexicon Event Structures into VerbNet0
Multitask Parsing Across Semantic RepresentationsCode0
An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols0
SPADE: Evaluation Dataset for Monolingual Phrase Alignment0
Don't Annotate, but Validate: a Data-to-Text Method for Capturing Event Data0
Towards AMR-BR: A SemBank for Brazilian Portuguese Language0
Creation of a Balanced State-of-the-Art Multilayer Corpus for NLUCode0
Construction of Large-scale English Verbal Multiword Expression Annotated CorpusCode0
Huge Automatically Extracted Training-Sets for Multilingual Word SenseDisambiguation0
EventWiki: A Knowledge Base of Major Events0
A Parser for LTAG and Frame SemanticsCode0
QUEST: A Natural Language Interface to Relational Databases0
Semantic Parsing with Syntax- and Table-Aware SQL Generation0
Cross-lingual Semantic Parsing0
Decoupling Structure and Lexicon for Zero-Shot Semantic ParsingCode0
Learning Joint Semantic Parsers from Disjoint DataCode0
Human Semantic Parsing for Person Re-identification0
Polyglot Semantic Parsing in APIsCode0
Semantic Parsing Natural Language into SPARQL: Improving Target Language Representation with Neural Attention0
Cache Transition Systems for Graph Parsing0
AMUSE: Multilingual Semantic Parsing for Question Answering over Linked DataCode0
From Characters to Time Intervals: New Paradigms for Evaluation and Neural Parsing of Time NormalizationsCode0
Beyond Word Embeddings: Learning Entity and Concept Representations from Large Scale Knowledge Bases0
Vietnamese Semantic Role LabellingCode0
Weakly-supervised Semantic Parsing with Abstract ExamplesCode0
The Challenge of Composition in Distributional and Formal Semantics0
Improving Black-box Speech Recognition using Semantic Parsing0
SLING: A framework for frame semantic parsingCode0
Towards Universal Semantic Tagging0
Training an adaptive dialogue policy for interactive learning of visually grounded word meanings0
Object-oriented Neural Programming (OONP) for Document Understanding0
Abductive Matching in Question Answering0
A Unified Framework for Structured Prediction: From Theory to Practice0
A Joint Sequential and Relational Model for Frame-Semantic Parsing0
QUINT: Interpretable Question Answering over Knowledge Bases0
Evaluating Hierarchies of Verb Argument Structure with Hierarchical Clustering0
Neural Semantic Parsing with Type Constraints for Semi-Structured TablesCode0
Recovering Question Answering Errors via Query Revision0
Deep Neural Solver for Math Word Problems0
Dealing with Co-reference in Neural Semantic ParsingCode0
Cross-Lingual SRL Based upon Universal Dependencies0
A Statistical Machine Translation Model with Forest-to-Tree Algorithm for Semantic Parsing0
Maximum Margin Reward Networks for Learning from Explicit and Implicit Supervision0
Joint Concept Learning and Semantic Parsing from Natural Language Explanations0
Beyond Sentential Semantic Parsing: Tackling the Math SAT with a Cascade of Tree Transducers0
Embedded Semantic Lexicon Induction with Joint Global and Local Optimization0
Semantic Frames and Visual Scenes: Learning Semantic Role Inventories from Image and Video Descriptions0
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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