Triple

T32027826
Position Surface form Disambiguated ID Type / Status
Subject Mount Dulang-dulang E817864 entity
Predicate rankingByElevationInPhilippines P181356 FINISHED
Object second highest mountain in the Philippines LITERAL 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: second highest mountain in the Philippines | Statement: [Mount Dulang-dulang, rankingByElevationInPhilippines, second highest mountain in the Philippines]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rankingByElevationInPhilippines
Context triple: [Mount Dulang-dulang, rankingByElevationInPhilippines, second highest mountain in the Philippines]
  • A. rankByAreaInPhilippines
    Indicates the relative ordering of entities based on their area size specifically within the Philippines.
  • B. rankByBasinSizeInPhilippines
    Indicates the ordering of items based on the size of their basins specifically within the Philippines.
  • C. elevationOfHighestPeak_ft
    Indicates the height, in feet, of the tallest peak associated with the given entity.
  • D. mountainHeight
    Indicates the vertical elevation or height of a mountain, typically measured from sea level.
  • E. mountainElevationContext
    Indicates the contextual relationship between a mountain and its elevation, such as how high it is relative to surrounding terrain or reference points.
  • F. None of above. chosen

Provenance (4 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_69f348fb04e4819081f4eab040ed7959 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f7688dd3d08190ad13d0e780570a1c completed May 3, 2026, 3:23 p.m.
PD Predicate disambiguation batch_69f767fcf2f881908bacc7bfc38e68a5 completed May 3, 2026, 3:21 p.m.
PDg Predicate description generation batch_69f7688cea58819098bdfd7c80df7634 completed May 3, 2026, 3:23 p.m.
Created at: May 1, 2026, 12:17 a.m.