Triple

T12878322
Position Surface form Disambiguated ID Type / Status
Subject Cerro El Ávila E308021 entity
Predicate hasAccessPoint P1985 FINISHED
Object Galipán E1004861 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: Galipán | Statement: [Cerro El Ávila, hasAccessPoint, Galipán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Galipán
Context triple: [Cerro El Ávila, hasAccessPoint, Galipán]
  • A. Galipán chosen
    Galipán is a small mountain village in Venezuela known for its cool climate, flower and strawberry production, and scenic views over Caracas and the Caribbean coast.
  • B. Guamúchil
    Guamúchil is a city in the Mexican state of Sinaloa known as a regional commercial and agricultural center.
  • C. Atzacan
    Atzacan is a municipality in the Mexican state of Veracruz that forms part of the greater Orizaba metropolitan region.
  • D. Tecolotlán
    Tecolotlán is a municipality and town in the state of Jalisco, Mexico, known for its rural landscapes, traditional culture, and location within the Sierra de Amula region.
  • E. Tuxpan
    Tuxpan is a town and municipality in the Mexican state of Nayarit, known for its agricultural economy and traditional cultural festivals.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69bba33c081909c0050ff7b868a8e completed May 3, 2026, 12:50 a.m.
Created at: April 9, 2026, 5:38 p.m.