Triple

T9745340
Position Surface form Disambiguated ID Type / Status
Subject Bukidnon highlands E236291 entity
Predicate locatedIn P40 FINISHED
Object Bukidnon E236288 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: Bukidnon | Statement: [Bukidnon highlands, locatedIn, Bukidnon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bukidnon
Context triple: [Bukidnon highlands, locatedIn, Bukidnon]
  • A. Bukidnon chosen
    Bukidnon is a landlocked, mountainous province in the Philippines known for its vast agricultural plantations, cool climate, and scenic highland landscapes.
  • B. Bontoc
    Bontoc is an Austronesian language spoken by the Bontoc people in the Mountain Province of the northern Philippines.
  • C. Bontoc
    Bontoc is a coastal municipality in the province of Southern Leyte in the Philippines known for its agricultural economy and rural communities.
  • D. Yakan
    Yakan is an Austronesian language spoken primarily by the Yakan people of Basilan and nearby areas in the southern Philippines.
  • E. Sugbuanon
    Sugbuanon refers to the Cebuano people, a Visayan ethnolinguistic group from the central and southern Philippines known for speaking the Cebuano language.
  • 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f2f8e648190ad94c940f9dc1de0 completed April 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d2285b4c8081908aba8a074288ee00 completed April 5, 2026, 9:16 a.m.
Created at: March 30, 2026, 8:23 p.m.