concept

dependency parsing

Also known as: dependency parser

Facts (10)

Sources

Efficient Knowledge Graph Construction and Retrieval from ... - arXiv arxiv.org arXiv Aug 7, 2025 8 facts

referenceThe GraphRAG architecture proposed in the paper utilizes a two-step methodology: (i) an interchangeable knowledge graph framework supporting both LLM-based generation and lightweight dependency parser-based construction, and (ii) a cascaded retrieval system combining one-hop graph traversal with dense vector-based node re-ranking.

claimSyntactic methods like dependency parsing, as cited in Bunescu and Mooney (2005), Ningthoujam et al. (2019), and Nooralahzadeh et al. (2018), provide scalable alternatives for lightweight graph construction.

claimThe TripleExtractor system utilizes the SpaCy dependency parser for information extraction because SpaCy is designed for industrial use, offers high-speed performance, and includes a state-of-the-art dependency parser suitable for open-ended information extraction.

claimThe dependency parsing approach used in the TripleExtractor system is domain-agnostic, allowing it to be applied across various domains without requiring domain-specific training or customization.

claimDependency parsing, while a lightweight and scalable method for extracting knowledge triples, may fail to capture context-dependent or implicit relations that are not directly expressed in surface syntax.

claimThe DependencyExtractor component converts syntactic trees generated by a dependency parser into structured knowledge triples, such as identifying {SAP, launch, Joule_for_Consultants} from the input "SAP launched Joule for Consultants".

procedureThe GraphRAG system constructs knowledge graphs using either a high-quality, computationally expensive LLM-based extractor or a lightweight, cost-effective dependency-parser-based builder.

claimThe TripleExtractor system allows users to choose between commercial LLMs (GPT-4o and Sonnet) or a dependency parser-based approach for extracting knowledge triples.

Combining large language models with enterprise knowledge graphs frontiersin.org Frontiers Aug 26, 2024 1 fact

referenceThe paper 'Named entity recognition as dependency parsing' by Yu et al. (2020) proposes framing the task of named entity recognition as a dependency parsing problem.

Patterns in the Transition From Founder-Leadership to Community ... arxiv.org arXiv Feb 5, 2026 1 fact

referenceThe NLP4Gov toolkit, as described by Chakraborti et al. (2024a, 2024b), extracts institutional components from text by combining dependency parsing with semantic role labeling to parse unitary institutional statements into IG components.