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
Understanding the Effect of Algorithm Transparency of Model Explanations in Text-to-SQL Semantic Parsing0
Geo-Semantic-Parsing: AI-powered geoparsing by traversing semantic knowledge graphs0
Creativity or Brute Force? Using Brainteasers as a Window into the Problem-Solving Abilities of Large Language Models0
3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-scale 3D Point Clouds0
3D Semantic Parsing of Large-Scale Indoor Spaces0
A Bayesian Approach to Unsupervised Semantic Role Induction0
Abductive Matching in Question Answering0
Accurate polyglot semantic parsing with DAG grammars0
Accurate SHRG-Based Semantic Parsing0
A Chinese Multi-type Complex Questions Answering Dataset over Wikidata0
A Comparative Analysis of Knowledge-Intensive and Data-Intensive Semantic Parsers0
A Comparison of the Events and Relations Across ACE, ERE, TAC-KBP, and FrameNet Annotation Standards0
A Conditional Random Field-based Traditional Chinese Base Phrase Parser for SIGHAN Bake-off 2012 Evaluation0
A constrained graph algebra for semantic parsing with AMRs0
A Corpus and Semantic Parser for Multilingual Natural Language Querying of OpenStreetMap0
A Corpus of Preposition Supersenses0
Active Dialogue Simulation in Conversational Systems0
Active learning for deep semantic parsing0
Active Learning for Multilingual Semantic Parser0
AdaNSP: Uncertainty-driven Adaptive Decoding in Neural Semantic Parsing0
Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Prompting0
Adapting a FrameNet Semantic Parser for Spoken Language Understanding Using Adversarial Learning0
Adapting Discriminative Reranking to Grounded Language Learning0
Adaptive Self-training for Few-shot Neural Sequence Labeling0
Adaptive Self-training for Neural Sequence Labeling with Few Labels0
A Data Efficient End-To-End Spoken Language Understanding Architecture0
Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation0
Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation0
A Deep Architecture for Semantic Parsing0
A Discriminative Graph-Based Parser for the Abstract Meaning Representation0
A Double-Graph Based Framework for Frame Semantic Parsing0
ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics0
Advancing Seq2seq with Joint Paraphrase Learning0
A Full End-to-End Semantic Role Labeler, Syntactic-agnostic Over Syntactic-aware?0
A Globally Normalized Neural Model for Semantic Parsing0
A Joint Sequential and Relational Model for Frame-Semantic Parsing0
A Knowledge-Guided Framework for Frame Identification0
ALB at SemEval-2018 Task 10: A System for Capturing Discriminative Attributes0
Aligning Formal Meaning Representations with Surface Strings for Wide-Coverage Text Generation0
Alpage: Transition-based Semantic Graph Parsing with Syntactic Features0
Alto: Rapid Prototyping for Parsing and Translation0
A Methodology for Creating Question Answering Corpora Using Inverse Data Annotation0
A Multi-layer LSTM-based Approach for Robot Command Interaction Modeling0
A Multimodal LDA Model integrating Textual, Cognitive and Visual Modalities0
Analyse s\'emantique robuste par apprentissage antagoniste pour la g\'en\'eralisation de domaine (Robust Semantic Parsing with Adversarial Learning for Domain Generalization )0
An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols0
An Annotation Scheme for Quantifier Scope Disambiguation0
An Automatic Method for Building a Data-to-Text Generator0
An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global Knowledge0
A Neural Approach to KGQA via SPARQL Silhouette Generation0
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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