Triple

T13921607
Position Surface form Disambiguated ID Type / Status
Subject Apayao E334758 entity
Predicate hasMunicipality P847 FINISHED
Object Kabugao E1069669 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: Kabugao | Statement: [Apayao, hasMunicipality, Kabugao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabugao
Context triple: [Apayao, hasMunicipality, Kabugao]
  • A. Kabugao
    Kabugao is a dialect of the Isnag language spoken by indigenous communities in the northern Philippines.
  • B. Kabugao chosen
    Kabugao is a municipality in the Philippines that serves as the administrative and political center of the province of Apayao.
  • C. Kabuntalan
    Kabuntalan is a municipality in the province of Maguindanao del Norte in the Philippines, known for its location along the Rio Grande de Mindanao and its predominantly Maguindanaon population.
  • D. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • E. Guanito
    Guanito is a rural municipal district within the San Juan de la Maguana municipality in the San Juan Province of the Dominican Republic.
  • 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2aa5c1f481908a9d8786872f08fe completed April 14, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69fba1c45ba4819096233570d8d4afec completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:16 p.m.