Triple

T13150443
Position Surface form Disambiguated ID Type / Status
Subject San Fernando Hill E312448 entity
Predicate near P350 FINISHED
Object San Fernando city centre E79508 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: San Fernando city centre | Statement: [San Fernando Hill, near, San Fernando city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Fernando city centre
Context triple: [San Fernando Hill, near, San Fernando city centre]
  • A. San Fernando chosen
    San Fernando is a major industrial and commercial city located in the southern part of Trinidad, known for its energy sector and bustling urban center.
  • B. San Fernando
    San Fernando is a locality within the municipality of Huixquilucan in the State of Mexico, forming part of the greater Mexico City metropolitan area.
  • C. San Fernando
    San Fernando is a coastal municipality in the Philippine province of Masbate, known for its rural communities and fishing-based local economy.
  • D. San Fernando
    San Fernando is a principal urban center and agricultural hub in central Chile’s O’Higgins Region.
  • E. San Fernando
    San Fernando is a small Andean town in Ecuador’s Azuay Province, known for its rural highland landscapes and traditional agricultural communities.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bd1fc408190b4b5ca973bcee403 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eaea3f888190b47ed7bf1c52e7e7 completed May 3, 2026, 6:27 a.m.
Created at: April 9, 2026, 9:11 p.m.