Triple

T18002849
Position Surface form Disambiguated ID Type / Status
Subject Mount Data E430669 entity
Predicate locatedNear P294 FINISHED
Object Buguias, Benguet 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: Buguias, Benguet | Statement: [Mount Data, locatedNear, Buguias, Benguet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buguias, Benguet
Context triple: [Mount Data, locatedNear, Buguias, Benguet]
  • A. Buguias, Benguet chosen
    Buguias, Benguet is a highland farming municipality in the Philippines’ Cordillera region, known for its vegetable production and cool mountainous climate.
  • B. Kabayan, Benguet
    Kabayan, Benguet is a mountainous municipality in the Philippines known for its rice terraces, cultural heritage, and the famous Kabayan mummy caves.
  • C. La Trinidad, Benguet
    La Trinidad, Benguet is a highland municipality in the Philippines known as the provincial capital and for its cool climate, strawberry farms, and proximity to Baguio City.
  • D. Atok, Benguet
    Atok, Benguet is a high-altitude municipality in the Philippines known for its cool climate, mountainous landscapes, and scenic vegetable and flower farms.
  • E. Itogon
    Itogon is a mountainous municipality in Benguet province in the Philippines, known for its mining industry and scenic river valleys.
  • 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b3ea60608190b977644e946407b7 completed April 19, 2026, 10:52 a.m.
Created at: April 10, 2026, 10:23 a.m.