Triple

T9606218
Position Surface form Disambiguated ID Type / Status
Subject Luo people of Kenya E231976 entity
Predicate sportingContribution P17882 FINISHED
Object football in Kenya 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: football in Kenya | Statement: [Luo people of Kenya, sportingContribution, football in Kenya]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: sportingContribution
Context triple: [Luo people of Kenya, sportingContribution, football in Kenya]
  • A. sponsorSport
    Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
  • B. sportsInvolvement chosen
    Indicates the nature or extent of an entity’s participation in, association with, or role within a sport or sporting activity.
  • C. sportingAssociation
    Indicates a formal relationship in which an organization serves as a governing, organizing, or affiliating body for sports activities, teams, or events.
  • D. sportsAndRecreation
    Indicates a relationship where an entity is associated with, involved in, or designated for sports or recreational activities.
  • E. sportFocus
    Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
  • 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_69ca8485a90c819094fe40b42fde9d70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a6006d48190adc03306533b9be6 completed April 1, 2026, 10:21 p.m.
PD Predicate disambiguation batch_69ccd5a6fd2481908efd131e207b8143 completed April 1, 2026, 8:21 a.m.
Created at: March 30, 2026, 8:08 p.m.