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
SemEval 2019 Shared Task: Cross-lingual Semantic Parsing with UCCA - Call for Participation0
SemEval-2019 Task 1: Cross-lingual Semantic Parsing with UCCA0
Semi-Supervised Lexicon Learning for Wide-Coverage Semantic Parsing0
Sentence Rewriting for Semantic Parsing0
Sequence-based Structured Prediction for Semantic Parsing0
SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models0
ShrdLite: Semantic Parsing Using a Handmade Grammar0
Simple and Effective Text Simplification Using Semantic and Neural Methods0
Simple, Fast Semantic Parsing with a Tensor Kernel0
Single Classifier Approach for Verb Sense Disambiguation based on Generalized Features0
Skill-Based Few-Shot Selection for In-Context Learning0
Software Requirements: A new Domain for Semantic Parsers0
SPADE: Evaluation Dataset for Monolingual Phrase Alignment0
SPAGHETTI: Open-Domain Question Answering from Heterogeneous Data Sources with Retrieval and Semantic Parsing0
Span-based Hierarchical Semantic Parsing for Task-Oriented Dialog0
Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing0
SPARQL query generation for complex question answering with BERT and BiLSTM-based model0
Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback0
Splitting compounds with ngrams0
State-of-the-Art Kernels for Natural Language Processing0
Statistical Models for Frame-Semantic Parsing0
STOP: A dataset for Spoken Task Oriented Semantic Parsing0
Structural generalization in COGS: Supertagging is (almost) all you need0
Structural Transfer Learning in NL-to-Bash Semantic Parsers0
Structured Case-based Reasoning for Inference-time Adaptation of Text-to-SQL parsers0
Structured Context and High-Coverage Grammar for Conversational Question Answering over Knowledge Graphs0
SUBS: Subtree Substitution for Compositional Semantic Parsing0
Supertagging: Introduction, learning, and application0
Supertagging With LSTMs0
Supervised Clustering of Questions into Intents for Dialog System Applications0
SXUCFN-Core: STS Models Integrating FrameNet Parsing Information0
Syn-QG: Syntactic and Shallow Semantic Rules for Question Generation0
Syntactic Question Abstraction and Retrieval for Data-Scarce Semantic Parsing0
SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-Domain Text-to-SQL Task0
SystemT: Declarative Text Understanding for Enterprise0
T5QL: Taming language models for SQL generation0
TARGA: Targeted Synthetic Data Generation for Practical Reasoning over Structured Data0
Temporal Knowledge Graph Question Answering: A Survey0
Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks0
The 2020 Bilingual, Bi-Directional WebNLG+ Shared Task: Overview and Evaluation Results (WebNLG+ 2020)0
The aNALoGuE Challenge: Non Aligned Language GEneration0
The APVA-TURBO Approach To Question Answering in Knowledge Base0
The Arm-Swing Is Discriminative in Video Gait Recognition for Athlete Re-Identification0
The Best of Both Worlds: Combining Human and Machine Translations for Multilingual Semantic Parsing with Active Learning0
The Challenge of Composition in Distributional and Formal Semantics0
The Effects of Lexical Resource Quality on Preference Violation Detection0
The First Shared Task on Discourse Representation Structure Parsing0
The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers0
The Groningen Meaning Bank0
The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities0
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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