Triple

T7983397
Position Surface form Disambiguated ID Type / Status
Subject RFEF E185627 entity
Predicate organizes P123 FINISHED
Object Tercera Federación E559682 NE 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: Tercera Federación | Statement: [RFEF, organizes, Tercera Federación]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tercera Federación
Context triple: [RFEF, organizes, Tercera Federación]
  • A. Tercera Federación chosen
    Tercera Federación is a lower-tier division in the Spanish football league system that serves as a regionalized competition beneath the national professional levels.
  • B. Segunda Federación
    Segunda Federación is a Spanish football league that serves as one of the lower tiers in the national league system beneath the professional divisions.
  • C. Primera Federación
    Primera Federación is a Spanish football league that serves as the third tier of the national league system, sitting below La Liga and the Segunda División.
  • D. Unión de Tula
    Unión de Tula is a municipality and town in the state of Jalisco, Mexico, known for its agricultural economy and location within the Sierra de Amula region.
  • E. Unión Española
    Unión Española is a traditional and historically successful Chilean football club based in Santiago.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca829a2cfc819083d591d58ec04075 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c2a1aa881909c3cea280dff38f5 completed March 31, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63b96ed48190b752865ef3855e46 completed April 1, 2026, 12:15 a.m.
Created at: March 30, 2026, 5:15 p.m.