Triple

T17777186
Position Surface form Disambiguated ID Type / Status
Subject Punilla E443801 entity
Predicate hasMunicipality P847 FINISHED
Object San Fabián NE NERFINISHED

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: San Fabián | Statement: [Punilla, hasMunicipality, San Fabián]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Fabián
Context triple: [Punilla, hasMunicipality, San Fabián]
  • A. San Fabián chosen
    San Fabián is a rural commune and town in Chile’s Ñuble Region, known for its mountainous landscapes and outdoor recreation opportunities.
  • B. San Fabian
    San Fabian is a coastal municipality in the province of Pangasinan, Philippines, known for its beaches along the Lingayen Gulf.
  • C. Saint Fermín
    Saint Fermín is a Catholic saint and martyr traditionally venerated as the first bishop of Pamplona and the patron saint of the famous running of the bulls festival held in his honor in Spain.
  • D. Atanacio
    Atanacio is the Spanish given name of Hall of Fame Cuban-American baseball player Tony Pérez.
  • E. San Gerardo
    San Gerardo is a small municipality in eastern El Salvador known for its rural character and location within the San Miguel Department.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871e06a481909cf6d59e49dc21c5 completed April 19, 2026, 7:41 a.m.
Created at: April 10, 2026, 10:12 a.m.