Triple

T11684243
Position Surface form Disambiguated ID Type / Status
Subject Agusan del Norte E277697 entity
Predicate hasLargestCity P235 FINISHED
Object Butuan E124942 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: Butuan | Statement: [Agusan del Norte, hasLargestCity, Butuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Butuan
Context triple: [Agusan del Norte, hasLargestCity, Butuan]
  • A. Butuan chosen
    Butuan is a historically significant city in the Caraga region of northeastern Mindanao in the Philippines, known for its rich pre-colonial heritage and archaeological sites.
  • B. Buruanga
    Buruanga is a coastal municipality in the province of Aklan in the Philippines, known for its scenic beaches and proximity to the tourist island of Boracay.
  • C. Guiguinto
    Guiguinto is a municipality in the province of Bulacan in the Philippines, known for its rapid urbanization and ornamental plant industry.
  • D. Liboi
    Liboi is a small Kenyan border town in the arid northeast near Somalia, serving as a local trading and transit point.
  • E. Tabogon
    Tabogon is a coastal municipality in the province of Cebu in the Philippines, known for its agricultural lands and scenic seaside areas.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a463f6448190a4c8e1651a2bd905 completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef142269d08190a9e5cf8d6268168b completed April 27, 2026, 7:45 a.m.
Created at: April 8, 2026, 9:40 p.m.