e5a532a8bc
- Introduced `test_nlp_extractor.py` with unit tests for the InstitutionExtractor, covering various extraction patterns (ISIL, Wikidata, VIAF, city names) and ensuring proper classification of institutions (museum, library, archive). - Added tests for extracted entities and result handling to validate the extraction process. - Created `test_partnership_rdf_integration.py` to validate the end-to-end process of extracting partnerships from a conversation and exporting them to RDF format. - Implemented tests for temporal properties in partnerships and ensured compliance with W3C Organization Ontology patterns. - Verified that extracted partnerships are correctly linked with PROV-O provenance metadata.
122 lines
4.1 KiB
YAML
122 lines
4.1 KiB
YAML
---
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# Example: Conference paper from ISWC (International Semantic Web Conference)
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# Reference: Hogan, A., et al. (2021). Knowledge Graphs.
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# ACM Computing Surveys, 54(4), 1-37. https://doi.org/10.1145/3447772
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# (Published version of ISWC 2020 keynote)
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- publication_id: https://doi.org/10.1145/3447772
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title: "Knowledge Graphs"
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publication_type: REVIEW_ARTICLE
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authors:
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- person_id: https://orcid.org/0000-0003-0103-6247
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person_name: "Aidan Hogan"
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orcid: "0000-0003-0103-6247"
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affiliation:
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organization_id: https://ror.org/05v62cm79
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organization_name: "Universidad de Chile"
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ror_id: "https://ror.org/05v62cm79"
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location: "CL"
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- person_id: https://orcid.org/0000-0002-8356-9309
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person_name: "Eva Blomqvist"
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orcid: "0000-0002-8356-9309"
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affiliation:
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organization_id: https://ror.org/03yghzc09
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organization_name: "Linköping University"
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ror_id: "https://ror.org/03yghzc09"
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location: "SE"
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- person_id: https://orcid.org/0000-0002-5711-3091
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person_name: "Michael Cochez"
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orcid: "0000-0002-5711-3091"
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affiliation:
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organization_id: https://ror.org/04pp8hn57
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organization_name: "Vrije Universiteit Amsterdam"
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ror_id: "https://ror.org/04pp8hn57"
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location: "NL"
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published_in: https://w3id.org/heritage/journal/acm-csur
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publication_date: "2021-07-01"
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volume: "54"
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issue: "4"
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page_range: "1-37"
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article_number: "71"
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doi: "10.1145/3447772"
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url: "https://dl.acm.org/doi/10.1145/3447772"
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abstract: >-
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In this article, we provide a comprehensive introduction to knowledge
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graphs, which have recently garnered significant attention from both
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industry and academia in scenarios that require exploiting diverse,
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dynamic, large-scale collections of data. After a general introduction,
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we motivate and contrast various graph-based data models, as well as
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graph query languages that are used to define and access knowledge graphs.
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keywords:
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- "Knowledge Graphs"
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- "Semantic Web"
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- "RDF"
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- "SPARQL"
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- "Ontologies"
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- "Linked Data"
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- "Graph Databases"
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open_access_status: OPEN_ACCESS_REPOSITORY
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citations:
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- citation_id: https://w3id.org/heritage/citation/kg-survey-cites-rdf
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citing_work: https://doi.org/10.1145/3447772
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cited_work: https://www.w3.org/TR/rdf11-concepts/
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citation_type: CITES_AS_EVIDENCE
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- citation_id: https://w3id.org/heritage/citation/kg-survey-cites-sparql
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citing_work: https://doi.org/10.1145/3447772
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cited_work: https://www.w3.org/TR/sparql11-query/
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citation_type: CITES_AS_EVIDENCE
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- citation_id: https://w3id.org/heritage/citation/kg-survey-extends
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citing_work: https://doi.org/10.1145/3447772
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cited_work: https://doi.org/10.1007/978-3-540-76298-0_52
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citation_type: EXTENDS
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document_sections:
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- section_id: https://w3id.org/heritage/section/kg-survey-intro
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section_type: INTRODUCTION
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section_title: "Introduction"
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section_order: 1
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- section_id: https://w3id.org/heritage/section/kg-survey-models
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section_type: METHODS
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section_title: "Data Graphs"
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section_order: 2
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- section_id: https://w3id.org/heritage/section/kg-survey-schema
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section_type: METHODS
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section_title: "Schema, Identity, and Context"
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section_order: 3
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- section_id: https://w3id.org/heritage/section/kg-survey-deductive
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section_type: METHODS
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section_title: "Deductive Knowledge"
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section_order: 4
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- section_id: https://w3id.org/heritage/section/kg-survey-inductive
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section_type: METHODS
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section_title: "Inductive Knowledge"
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section_order: 5
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- section_id: https://w3id.org/heritage/section/kg-survey-conclusion
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section_type: CONCLUSION
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section_title: "Conclusion"
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section_order: 6
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provenance:
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data_source: CSV_REGISTRY
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data_tier: TIER_1_AUTHORITATIVE
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extraction_date: "2025-11-09T15:15:00Z"
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extraction_method: "Manual curation from ACM Digital Library metadata"
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confidence_score: 1.0
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