Triple

T9856457
Position Surface form Disambiguated ID Type / Status
Subject Keeneland Race Course E239598 entity
Predicate hasStableArea P34773 FINISHED
Object Keeneland stable area 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: Keeneland stable area | Statement: [Keeneland Race Course, hasStableArea, Keeneland stable area]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasStableArea
Context triple: [Keeneland Race Course, hasStableArea, Keeneland stable area]
  • A. isStable
    Indicates that the state, condition, or configuration of an entity does not change significantly over time or under expected variations in its environment.
  • B. hasStabilityLevel
    Indicates that something possesses a particular degree or state of stability, often quantified or categorized along a defined scale.
  • C. stabilizedBy
    Indicates that an entity’s state, structure, or behavior is made more steady, secure, or resistant to change through the influence or support of another entity.
  • D. hasStandingArea chosen
    Indicates that an entity includes or provides a designated area where people can stand.
  • E. hasSubstantiveArea
    Indicates that one entity is associated with, or falls within, a particular substantive field or domain of activity, knowledge, or regulation.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb39864188190a2d8c0ee911f00c2 completed April 2, 2026, 12:08 a.m.
PD Predicate disambiguation batch_69cd1d7621d48190aa6a6f34399514b0 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:35 p.m.