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 551600 of 1202 papers

TitleStatusHype
Fast semantic parsing with well-typedness guarantees0
Fast Forward Through Opportunistic Incremental Meaning Representation Construction0
Fast and Accurate Capitalization and Punctuation for Automatic Speech Recognition Using Transformer and Chunk Merging0
Compositional Generalization in Dependency Parsing0
Extrinsic Evaluation of Machine Translation Metrics0
Compositional Generalization for Neural Semantic Parsing via Span-level Supervised Attention0
AskYourDB: An end-to-end system for querying and visualizing relational databases using natural language0
Extracting a bilingual semantic grammar from FrameNet-annotated corpora0
Exploring Unexplored Generalization Challenges for Cross-Database Semantic Parsing0
Compositional Generalization for Natural Language Interfaces to Web APIs0
Exploring Neural Models for Parsing Natural Language into First-Order Logic0
Exploring Graph-Algebraic CCG Combinators for Syntactic-Semantic AMR Parsing0
Exploring Example Selection for Few-shot Text-to-SQL Semantic Parsing0
A Sentence Is Worth a Thousand Pixels0
A Joint Sequential and Relational Model for Frame-Semantic Parsing0
A Corpus of Preposition Supersenses0
3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-scale 3D Point Clouds0
Understanding the Effect of Algorithm Transparency of Model Explanations in Text-to-SQL Semantic Parsing0
Exploiting Frame-Semantics and Frame-Semantic Parsing for Automatic Extraction of Typological Information from Descriptive Grammars of Natural Languages0
Explaining Large Language Model-Based Neural Semantic Parsers (Student Abstract)0
A Semantic Parsing Algorithm to Solve Linear Ordering Problems0
EventWiki: A Knowledge Base of Major Events0
Event Extraction as Frame-Semantic Parsing0
Evaluation Strategies for Computational Construction Grammars0
Comparing Representations of Semantic Roles for String-To-Tree Decoding0
Ar-Spider: Text-to-SQL in Arabic0
Evaluating the Impact of Model Scale for Compositional Generalization in Semantic Parsing0
Comparing Knowledge-Intensive and Data-Intensive Models for English Resource Semantic Parsing0
Combining Improvements for Exploiting Dependency Trees in Neural Semantic Parsing0
A Robust Approach to Aligning Heterogeneous Lexical Resources0
Evaluating Persian Tokenizers0
Combining Formal and Distributional Models of Temporal and Intensional Semantics0
Argument structure of adverbial derivatives in Russian0
A Corpus and Semantic Parser for Multilingual Natural Language Querying of OpenStreetMap0
Evaluating Hierarchies of Verb Argument Structure with Hierarchical Clustering0
Evaluating Byte and Wordpiece Level Models for Massively Multilingual Semantic Parsing0
EUSP: An Easy-to-Use Semantic Parsing PlatForm0
ERSOM: A Structural Ontology Matching Approach Using Automatically Learned Entity Representation0
A Probabilistic-Logic based Commonsense Representation Framework for Modelling Inferences with Multiple Antecedents and Varying Likelihoods0
Error-Aware Interactive Semantic Parsing of OpenStreetMap0
Equation Parsing : Mapping Sentences to Grounded Equations0
CMU: Arc-Factored, Discriminative Semantic Dependency Parsing0
Enhancing The RATP-DECODA Corpus With Linguistic Annotations For Performing A Large Range Of NLP Tasks0
Classifying Temporal Relations with Simple Features0
Enhancing Text-to-SQL Capabilities of Large Language Models via Domain Database Knowledge Injection0
Self-Enhancing Multi-filter Sequence-to-Sequence Model0
Enhancing Key-Value Memory Neural Networks for Knowledge Based Question Answering0
CLASP: Few-Shot Cross-Lingual Data Augmentation for Semantic Parsing0
A Pointer Network Architecture for Context-Dependent Semantic Parsing0
A Globally Normalized Neural Model for Semantic Parsing0
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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