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Semantic Parsing
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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
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/aliwister/ast-icl
공식 코드Semantic Captioning: Benchmark Dataset and Graph-Aware Few-Shot In-Context Learning for SQL2Text
https://github.com/allenai/code-semparse
공식 코드Leveraging Code to Improve In-context Learning for Semantic Parsing
https://github.com/allenai/open_vocab_semparse
공식 코드Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge
https://github.com/amazon-research/resource-constrained-naturalized-semantic-parsing
공식 코드https://github.com/amazon-research/semantic-parsing-as-abstractive-qa
공식 코드Compositional Task-Oriented Parsing as Abstractive Question Answering
https://github.com/amazon-science/handling-ontology-gaps-in-semantic-parsing
공식 코드https://github.com/ameyagodbole/long-tail-likelihood-splits
공식 코드Benchmarking Long-tail Generalization with Likelihood Splits
https://github.com/amikael/ncdigraphs
공식 코드Generic Axiomatization of Families of Noncrossing Graphs in Dependency Parsing
https://github.com/amolk/spider-schema-gnn/blob/discriminator/GNNDiscrimNet.ipynb
공식 코드Bertrand-DR: Improving Text-to-SQL using a Discriminative Re-ranker
https://github.com/amzn/seqzero
공식 코드SeqZero: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models
https://github.com/andotalao24/multistage-collaborative-knowledge-distillation
공식 코드https://github.com/aozmh/crake
공식 코드Crake: Causal-Enhanced Table-Filler for Question Answering over Large Scale Knowledge Base
https://github.com/appier-research/i-need-help
공식 코드https://github.com/apple/ml-tree-dst
공식 코드https://github.com/arthurizijar/kb-coder
공식 코드Code-Style In-Context Learning for Knowledge-Based Question Answering
https://github.com/asaparov/fictionalgeoqa
공식 코드Towards General Natural Language Understanding with Probabilistic Worldbuilding
https://github.com/asaparov/grammar
공식 코드https://github.com/asaparov/parser
공식 코드https://github.com/asaparov/pwl
공식 코드Towards General Natural Language Understanding with Probabilistic Worldbuilding
https://github.com/awslabs/multilingual-top
공식 코드Multilingual Neural Semantic Parsing for Low-Resourced Languages
https://github.com/awslabs/unified-text2sql-benchmark
공식 코드https://github.com/ayush-pancholy/sister-help
공식 코드Sister Help: Data Augmentation for Frame-Semantic Role Labeling
https://github.com/babelscape/amr-alignment
공식 코드Cross-lingual AMR Aligner: Paying Attention to Cross-Attention
https://github.com/babelscape/amrs-assemble
공식 코드AMRs Assemble! Learning to Ensemble with Autoregressive Models for AMR Parsing
https://github.com/bahuia/sscl-text2sql
공식 코드https://github.com/bayer-group/text-to-sql-epi-ehr-naacl2024
공식 코드https://github.com/beachwang/dail-sql
공식 코드Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation
https://github.com/benbogin/spider-schema-gnn
공식 코드Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing
https://github.com/benbogin/spider-schema-gnn-global
공식 코드Global Reasoning over Database Structures for Text-to-SQL Parsing
https://github.com/benbogin/unobserved-local-structures
공식 코드Unobserved Local Structures Make Compositional Generalization Hard
https://github.com/benlipkin/probsem
공식 코드Evaluating statistical language models as pragmatic reasoners
https://github.com/bergen/edgetransformer
공식 코드https://github.com/berlino/grammar-prompting
공식 코드Grammar Prompting for Domain-Specific Language Generation with Large Language Models
https://github.com/berlino/tensor2struct-public
공식 코드https://github.com/berlino/weaksp_em19
공식 코드Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.