Triple

T253653
Position Surface form Disambiguated ID Type / Status
Subject Fray Jorge National Park E5390 entity
Predicate nearestCity P350 FINISHED
Object Ovalle E5387 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: Ovalle | Statement: [Fray Jorge National Park, nearestCity, Ovalle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ovalle
Context triple: [Fray Jorge National Park, nearestCity, Ovalle]
  • A. Ovalle chosen
    Ovalle is a Chilean city known as an agricultural and commercial center in the north-central part of the country.
  • B. La Calera
    La Calera is a Colombian town and municipality in the Andean department of Cundinamarca, known for its mountainous landscapes and proximity to Bogotá.
  • C. Calama
    Calama is a city in northern Chile known as a key mining center and gateway to the Atacama Desert.
  • D. Arausio
    Arausio is the ancient Latin name for the town now known as Orange in southeastern France, historically notable for its Roman monuments and heritage.
  • E. Arica
    Arica is a major port city in far northern Chile, known for its dry climate, strategic location near the Peruvian border, and role as a commercial and transportation hub on the Pacific coast.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d5331b48190b3797fece8e60e20 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a40348b4f08190bdb3f7085d5db930 completed March 1, 2026, 9:13 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.