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 651700 of 1202 papers

TitleStatusHype
Bottom-Up Unranked Tree-to-Graph Transducers for Translation into Semantic Graphs0
Improving Semantic Dependency Parsing with Syntactic Features0
Exploring Graph-Algebraic CCG Combinators for Syntactic-Semantic AMR Parsing0
Parsing All: Syntax and Semantics, Dependencies and SpansCode0
Global Reasoning over Database Structures for Text-to-SQL ParsingCode0
A survey of cross-lingual features for zero-shot cross-lingual semantic parsing0
Don't paraphrase, detect! Rapid and Effective Data Collection for Semantic ParsingCode0
Establishing Strong Baselines for the New Decade: Sequence Tagging, Syntactic and Semantic Parsing with BERTCode0
Interpolated Convolutional Networks for 3D Point Cloud Understanding0
Fast and Accurate Capitalization and Punctuation for Automatic Speech Recognition Using Transformer and Chunk Merging0
Grammatical Sequence Prediction for Real-Time Neural Semantic Parsing0
Syntax-aware Neural Semantic Role LabelingCode0
Semantic Parsing with Dual LearningCode0
Learning Neural Sequence-to-Sequence Models from Weak Feedback with Bipolar Ramp LossCode0
A Comparative Analysis of Knowledge-Intensive and Data-Intensive Semantic Parsers0
Neural Semantic Parsing with Anonymization for Command Understanding in General-Purpose Service RobotsCode0
Latent Structure Models for Natural Language Processing0
Discourse Representation Parsing for Sentences and Documents0
AdaNSP: Uncertainty-driven Adaptive Decoding in Neural Semantic Parsing0
Reranking for Neural Semantic Parsing0
Complex Question Decomposition for Semantic ParsingCode0
Semantic expressive capacity with bounded memory0
Compositional Semantic Parsing Across Graphbanks0
Program Synthesis and Semantic Parsing with Learned Code IdiomsCode0
Semantically Driven Auto-completion0
Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing0
Unified Semantic Parsing with Weak SupervisionCode0
Multimodal Logical Inference System for Visual-Textual Entailment0
SParC: Cross-Domain Semantic Parsing in ContextCode0
Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization0
Context Dependent Semantic Parsing over Temporally Structured Data0
Enhancing Key-Value Memory Neural Networks for Knowledge Based Question Answering0
GCN-Sem at SemEval-2019 Task 1: Semantic Parsing using Graph Convolutional and Recurrent Neural Networks0
Content Differences in Syntactic and Semantic RepresentationCode0
UC Davis at SemEval-2019 Task 1: DAG Semantic Parsing with Attention-based Decoder0
Cross-lingual CCG InductionCode0
Iterative Search for Weakly Supervised Semantic Parsing0
T\"upa at SemEval-2019 Task1: (Almost) feature-free Semantic Parsing0
DANGNT@UIT.VNU-HCM at SemEval 2019 Task 1: Graph Transformation System from Stanford Basic Dependencies to Universal Conceptual Cognitive Annotation (UCCA)0
CUNY-PKU Parser at SemEval-2019 Task 1: Cross-Lingual Semantic Parsing with UCCACode0
Grammar-based Neural Text-to-SQL Generation0
Compositional pre-training for neural semantic parsing0
Generating Logical Forms from Graph Representations of Text and Entities0
Multi-Task Learning for Semantic Parsing with Cross-Domain Sketch0
Proceedings of the IWCS Shared Task on Semantic Parsing0
Questions in Dependent Type Semantics0
Linguistic Information in Neural Semantic Parsing with Multiple Encoders0
Context-Dependent Semantic Parsing over Temporally Structured DataCode0
Transition-based DRS Parsing Using Stack-LSTMs0
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural SupervisionCode0
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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