Triple

T3817498
Position Surface form Disambiguated ID Type / Status
Subject Winchester main campus E84291 entity
Predicate hasAdministrativeFacilities P32450 FINISHED
Object university administrative offices LITERAL 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: university administrative offices | Statement: [Winchester main campus, hasAdministrativeFacilities, university administrative offices]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAdministrativeFacilities
Context triple: [Winchester main campus, hasAdministrativeFacilities, university administrative offices]
  • A. hasFacilities
    Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
  • B. hasMaintenanceFacilities
    Indicates that one entity provides or contains facilities where the other entity can be serviced, repaired, or maintained.
  • C. administrativeFeature chosen
    Indicates that one entity serves as an administrative or governance-related feature, function, or attribute associated with another entity.
  • D. hasNotableFacility
    Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
  • E. hasAcademicFacilities
    Indicates that an entity provides or is equipped with academic facilities such as classrooms, laboratories, libraries, or other educational infrastructure.
  • F. None of above.

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_69aed931f5908190be2c07af66d4df25 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef188b474819087680db42b04ecdd completed March 9, 2026, 4:12 p.m.
PD Predicate disambiguation batch_69aee74a2bc081909b237df8b1e27653 completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:17 p.m.