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
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing0
Learning Compact Lexicons for CCG Semantic Parsing0
Learning Compositional Semantics for Open Domain Semantic Parsing0
Learning Cross-lingual Distributed Logical Representations for Semantic Parsing0
Learning Executable Semantic Parsers for Natural Language Understanding0
Learning Programmatic Idioms for Scalable Semantic Parsing0
Learning Semantic Correspondences in Technical Documentation0
Learning Structured Natural Language Representations for Semantic Parsing0
Learning the Semantics of Manipulation Action0
Learning to Decompose: Hypothetical Question Decomposition Based on Comparable Texts0
Learning to Interpret Natural Language Instructions0
Learning to Jointly Predict Ellipsis and Comparison Structures0
Learning to Make Inferences in a Semantic Parsing Task0
Learning to Map Dependency Parses to Abstract Meaning Representations0
Learning to Retrieve Iteratively for In-Context Learning0
Learning to Transpile AMR into SPARQL0
Learning to Transpile AMR into SPARQL0
Learning Web-based Procedures by Reasoning over Explanations and Demonstrations in Context0
Lemmatising Serbian as Category Tagging with Bidirectional Sequence Classification0
Leveraging Data Recasting to Enhance Tabular Reasoning0
Leveraging Domain-Independent Information in Semantic Parsing0
Lexicon-injected Semantic Parsing for Task-Oriented Dialog0
LIA: A Natural Language Programmable Personal Assistant0
Light Textual Inference for Semantic Parsing0
LIMIT-BERT : Linguistic Informed Multi-Task BERT0
Linguistic Generalizations are not Rules: Impacts on Evaluation of LMs0
Linguistic Information in Neural Semantic Parsing with Multiple Encoders0
Linking Named Entities to Any Database0
LLM+AL: Bridging Large Language Models and Action Languages for Complex Reasoning about Actions0
LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network0
Logical Parsing from Natural Language Based on a Neural Translation Model0
Logical Story Representations via FrameNet + Semantic Parsing0
Logical Story Representations via FrameNet + Semantic Parsing0
LOGICSEG: Parsing Visual Semantics with Neural Logic Learning and Reasoning0
LOR-KBGEN, A Hybrid Approach To Generating from the KBGen Knowledge-Base0
Low-Dimensional Discriminative Reranking0
Low-Dimensional Embeddings of Logic0
Low-Resource Compositional Semantic Parsing with Concept Pretraining0
Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing0
Low-Resource Task-Oriented Semantic Parsing via Intrinsic Modeling0
Machine Translation Aided Bilingual Data-to-Text Generation and Semantic Parsing0
Makadi: A Large-Scale Human-Labeled Dataset for Hindi Semantic Parsing0
Making Transformers Solve Compositional Tasks0
Making Transformers Solve Compositional Tasks0
MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging0
Matrix Factorization with Knowledge Graph Propagation for Unsupervised Spoken Language Understanding0
Maximum Margin Reward Networks for Learning from Explicit and Implicit Supervision0
MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text0
MCTS-KBQA: Monte Carlo Tree Search for Knowledge Base Question Answering0
Measuring and Mitigating Constraint Violations of In-Context Learning for Utterance-to-API 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