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 11011150 of 1202 papers

TitleStatusHype
The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities0
What are You Talking About? Text-to-Image Coreference0
Single Classifier Approach for Verb Sense Disambiguation based on Generalized Features0
Multilingual eXtended WordNet Knowledge Base: Semantic Parsing and Translation of Glosses0
Not an Interlingua, But Close: Comparison of English AMRs to Chinese and Czech0
Using C5.0 and Exhaustive Search for Boosting Frame-Semantic Parsing Accuracy0
The Multilingual Paraphrase Database0
Disambiguating Verbs by Collocation: Corpus Lexicography meets Natural Language Processing0
Predicate Matrix: extending SemLink through WordNet mappings0
NoSta-D Named Entity Annotation for German: Guidelines and Dataset0
HuRIC: a Human Robot Interaction Corpus0
UnixMan Corpus: A Resource for Language Learning in the Unix Domain0
The Norwegian Dependency Treebank0
The Procedure of Lexico-Semantic Annotation of Sk Treebank0
First approach toward Semantic Role Labeling for Basque0
Extracting a bilingual semantic grammar from FrameNet-annotated corpora0
REFRACTIVE: An Open Source Tool to Extract Knowledge from Syntactic and Semantic Relations0
Contextual Semantic Parsing using Crowdsourced Spatial Descriptions0
A Deep Architecture for Semantic Parsing0
Probabilistic Type Theory for Incremental Dialogue Processing0
Empirically-motivated Generalizations of CCG Semantic Parsing Learning Algorithms0
Inducing Example-based Semantic Frames from a Massive Amount of Verb Uses0
Classifying Temporal Relations with Simple Features0
Frame-Semantic Parsing0
Integrative Semantic Dependency Parsing via Efficient Large-scale Feature Selection0
First steps towards a Predicate Matrix0
Large-scale Semantic Parsing without Question-Answer Pairs0
A New Corpus and Imitation Learning Framework for Context-Dependent Semantic Parsing0
Cornell SPF: Cornell Semantic Parsing FrameworkCode0
Automatic classification of semantic patterns from the Pattern Dictionary of English Verbs0
The Groningen Meaning Bank0
Using Shallow Semantic Parsing and Relation Extraction for Finding Contradiction in Text0
Semantic Parsing on Freebase from Question-Answer Pairs0
Effectiveness and Efficiency of Open Relation Extraction0
A Multimodal LDA Model integrating Textual, Cognitive and Visual Modalities0
Scaling Semantic Parsers with On-the-Fly Ontology Matching0
MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text0
Lambda Dependency-Based Compositional Semantics0
Joint Video and Text Parsing for Understanding Events and Answering Queries0
LOR-KBGEN, A Hybrid Approach To Generating from the KBGen Knowledge-Base0
Interpreting Situated Dialogue Utterances: an Update Model that Uses Speech, Gaze, and Gesture Information0
An Automatic Method for Building a Data-to-Text Generator0
Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models0
Wordnet-Based Cross-Language Identification of Semantic Relations0
Answer Extraction by Recursive Parse Tree Descent0
Aligning Formal Meaning Representations with Surface Strings for Wide-Coverage Text Generation0
Identifying Pathological Findings in German Radiology Reports Using a Syntacto-semantic Parsing Approach0
Philosophers are Mortal: Inferring the Truth of Unseen Facts0
Leveraging Domain-Independent Information in Semantic Parsing0
Graph-based Semi-Supervised Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging0
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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