Triple

T9068273
Position Surface form Disambiguated ID Type / Status
Subject Simple Knowledge Organization System E217298 entity
Predicate abbreviation P43 FINISHED
Object SKOS E40098 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: SKOS | Statement: [Simple Knowledge Organization System, abbreviation, SKOS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SKOS
Context triple: [Simple Knowledge Organization System, abbreviation, SKOS]
  • A. SKOS chosen
    SKOS (Simple Knowledge Organization System) is a W3C standard model for representing and sharing knowledge organization systems such as thesauri, classification schemes, and subject headings on the Semantic Web.
  • B. OWL
    OWL (Web Ontology Language) is a W3C-recommended semantic web language used to define and share rich, machine-interpretable ontologies on the web.
  • C. Dublin Core
    Dublin Core is a widely used standard for describing digital resources through a simple, generic set of metadata elements to support discovery and interoperability across systems.
  • D. RDFS
    RDFS (RDF Schema) is a semantic web vocabulary language used to define the structure, classes, and properties of RDF data.
  • E. RDF
    RDF (Resource Description Framework) is a standard model for data interchange on the Web that represents information as subject–predicate–object triples to enable structured, machine-readable metadata and knowledge graphs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca83d5a7f48190b16c1e59bd43ede0 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc94bf4f2881908c881e6ee7203994 completed April 1, 2026, 3:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffddc5c288190b18c2ae1aece4ed6 completed April 3, 2026, 5:50 p.m.
Created at: March 30, 2026, 7:11 p.m.