Triple

T7423004
Position Surface form Disambiguated ID Type / Status
Subject RIF E171294 entity
Predicate hasComponent P35 FINISHED
Object RIF-RDF+OWL
RIF-RDF+OWL is a RIF dialect designed to enable rule interchange and interoperability with RDF and OWL-based Semantic Web data and ontologies.
E664396 NE FINISHED

How this triple was built (4 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: RIF-RDF+OWL | Statement: [RIF, hasComponent, RIF-RDF+OWL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RIF-RDF+OWL
Context triple: [RIF, hasComponent, RIF-RDF+OWL]
  • A. OWL 2 RL
    OWL 2 RL is a profile of the Web Ontology Language designed for scalable reasoning using rule-based systems, enabling efficient inference over large datasets.
  • B. OWL 2 Web Ontology Language
    OWL 2 Web Ontology Language is a W3C-standardized knowledge representation language used to create, share, and reason over rich ontologies on the Semantic Web.
  • C. OWL 2 Full
    OWL 2 Full is a highly expressive semantic web ontology language variant that fully integrates OWL with RDF, allowing powerful but undecidable reasoning over web data.
  • D. RDFS
    RDFS (RDF Schema) is a semantic web vocabulary language used to define the structure, classes, and properties of RDF data.
  • E. RDF 1.1 Semantics
    RDF 1.1 Semantics is a W3C specification that formally defines the meaning and logical foundations of RDF data, enabling consistent interpretation and reasoning across RDF graphs.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: RIF-RDF+OWL
Triple: [RIF, hasComponent, RIF-RDF+OWL]
Generated description
RIF-RDF+OWL is a RIF dialect designed to enable rule interchange and interoperability with RDF and OWL-based Semantic Web data and ontologies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: RIF-RDF+OWL
Target entity description: RIF-RDF+OWL is a RIF dialect designed to enable rule interchange and interoperability with RDF and OWL-based Semantic Web data and ontologies.
  • A. OWL 2 RL
    OWL 2 RL is a profile of the Web Ontology Language designed for scalable reasoning using rule-based systems, enabling efficient inference over large datasets.
  • B. OWL 2 Web Ontology Language
    OWL 2 Web Ontology Language is a W3C-standardized knowledge representation language used to create, share, and reason over rich ontologies on the Semantic Web.
  • C. OWL 2 Full
    OWL 2 Full is a highly expressive semantic web ontology language variant that fully integrates OWL with RDF, allowing powerful but undecidable reasoning over web data.
  • D. RDFS
    RDFS (RDF Schema) is a semantic web vocabulary language used to define the structure, classes, and properties of RDF data.
  • E. RDF 1.1 Semantics
    RDF 1.1 Semantics is a W3C specification that formally defines the meaning and logical foundations of RDF data, enabling consistent interpretation and reasoning across RDF graphs.
  • F. None of above. chosen

Provenance (5 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_69c68a625d048190af70eb8b63bec5a0 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2eece588190905774e7151edcb8 completed March 27, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81effc488819086336eea92604fa8 completed March 28, 2026, 6:33 p.m.
NEDg Description generation batch_69c81fe025d081909f2a5c4515c60f64 completed March 28, 2026, 6:37 p.m.
NED2 Entity disambiguation (via description) batch_69c824010104819081977e89d79ebb44 completed March 28, 2026, 6:54 p.m.
Created at: March 27, 2026, 3:12 p.m.