Triple

T14943386
Position Surface form Disambiguated ID Type / Status
Subject Ludgate Circus E372586 entity
Predicate hasCommercialBuildings P50976 FINISHED
Object yes 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: yes | Statement: [Ludgate Circus, hasCommercialBuildings, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCommercialBuildings
Context triple: [Ludgate Circus, hasCommercialBuildings, yes]
  • A. hasOfficeBuildings
    Indicates that one entity possesses, controls, or is associated with one or more office buildings.
  • B. hasCommercialInfrastructure chosen
    Indicates that an entity possesses or is equipped with facilities, systems, or structures that support commercial or business activities.
  • C. hasMultipleBuildings
    Indicates that an entity possesses, controls, or is associated with more than one distinct building.
  • D. hasMainBuildings
    Indicates that one entity possesses or is associated with one or more primary or principal buildings.
  • E. hasMunicipalBuildings
    Indicates that a place or jurisdiction possesses one or more buildings used for municipal or local government functions.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded68c1df0819084c0cd61b207d398 completed April 15, 2026, 12:06 a.m.
PD Predicate disambiguation batch_69de9a588c2c8190b1245a1c406f447c completed April 14, 2026, 7:49 p.m.
Created at: April 10, 2026, 2:38 a.m.