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 351400 of 1202 papers

TitleStatusHype
Compositional Generalization in Dependency Parsing0
Program Transfer for Answering Complex Questions over Knowledge BasesCode1
AutoNLU: Detecting, root-causing, and fixing NLU model errors0
Disentangled Sequence to Sequence Learning for Compositional GeneralizationCode0
SPaR.txt, a cheap Shallow Parsing approach for Regulatory textsCode0
Towards Theme Detection in Personal Finance Questions0
DeepA2: A Modular Framework for Deep Argument Analysis with Pretrained Neural Text2Text Language ModelsCode1
Self-Attentive Constituency Parsing for UCCA-based Semantic Parsing0
Compositional generalization in semantic parsing with pretrained transformersCode0
A Graph-Based Neural Model for End-to-End Frame Semantic ParsingCode1
Self-Enhancing Multi-filter Sequence-to-Sequence Model0
Cross-linguistically Consistent Semantic and Syntactic Annotation of Child-directed SpeechCode0
Awakening Latent Grounding from Pretrained Language Models for Semantic Parsing0
RETRONLU: Retrieval Augmented Task-Oriented Semantic Parsing0
Sister Help: Data Augmentation for Frame-Semantic Role LabelingCode0
Total Recall: a Customized Continual Learning Method for Neural Semantic ParsersCode0
PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language ModelsCode1
ReasonBERT: Pre-trained to Reason with Distant SupervisionCode1
Semantic Parsing in Task-Oriented Dialog with Recursive Insertion-based Encoder0
Graph-Based Decoding for Task Oriented Semantic Parsing0
Translate & Fill: Improving Zero-Shot Multilingual Semantic Parsing with Synthetic Data0
Memory-Based Semantic ParsingCode0
Finding needles in a haystack: Sampling Structurally-diverse Training Sets from Synthetic Data for Compositional GeneralizationCode0
Corpus Creation and Language Identification in Low-Resource Code-Mixed Telugu-English Text0
Structured Context and High-Coverage Grammar for Conversational Question Answering over Knowledge Graphs0
Complex Knowledge Base Question Answering: A SurveyCode1
DEXTER: Deep Encoding of External Knowledge for Named Entity Recognition in Virtual Assistants0
Focusing on Persons: Colorizing Old Images Learning from Modern Historical MoviesCode1
Kicktionary-LOME: A Domain-Specific Multilingual Frame Semantic Parsing Model for Football Language0
Making Transformers Solve Compositional Tasks0
Tiny Neural Models for Seq2SeqCode0
Compositional Generalization in Multilingual Semantic Parsing over WikidataCode1
Relation Aware Semi-autoregressive Semantic Parsing for NL2SQL0
Knowledge Informed Semantic Parsing for Conversational Question Answering0
Grammar-Constrained Neural Semantic Parsing with LR Parsers0
Joint Multi-Decoder Framework with Hierarchical Pointer Network for Frame Semantic Parsing0
Incorporating Compositionality and Morphology into End-to-End Models0
Value-Agnostic Conversational Semantic Parsing0
A Knowledge-Guided Framework for Frame Identification0
CogIE: An Information Extraction Toolkit for Bridging Texts and CogNetCode1
Code Generation from Natural Language with Less Prior Knowledge and More Monolingual DataCode1
Lexicon Learning for Few Shot Sequence ModelingCode1
ReTraCk: A Flexible and Efficient Framework for Knowledge Base Question AnsweringCode0
TAPEX: Table Pre-training via Learning a Neural SQL ExecutorCode1
Learning Algebraic Recombination for Compositional GeneralizationCode0
Enforcing Consistency in Weakly Supervised Semantic ParsingCode0
Assessing Data Efficiency in Task-Oriented Semantic Parsing0
Draw Me a Flower: Processing and Grounding Abstraction in Natural Language0
Semantic Parsing Natural Language into Relational Algebra0
AIT-QA: Question Answering Dataset over Complex Tables in the Airline IndustryCode1
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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