Triple

T17970627
Position Surface form Disambiguated ID Type / Status
Subject Aklanon people E449329 entity
Predicate primaryLocation P3231 FINISHED
Object Aklan 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: Aklan | Statement: [Aklanon people, primaryLocation, Aklan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aklan
Context triple: [Aklanon people, primaryLocation, Aklan]
  • A. Aklan chosen
    Aklan is a province in the Philippines known for the world-famous Boracay Island and its vibrant Ati-Atihan Festival.
  • B. Guimaras
    Guimaras is a small island province in the Philippines known for its mango production, coastal scenery, and predominantly Hiligaynon-speaking population.
  • C. Aklanon
    Aklanon is an Austronesian language spoken primarily in the province of Aklan in the central Philippines.
  • D. Apayao
    Apayao is a landlocked, mountainous province in the northern Philippines known for its rich indigenous culture, forests, and river systems.
  • E. Iloilo province
    Iloilo province is a province in the Western Visayas region of the Philippines known for its rich cultural heritage, historic churches, and vibrant coastal and agricultural communities.
  • 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b1fa67c48190936f20cea45e4599 completed April 19, 2026, 10:44 a.m.
Created at: April 10, 2026, 10:22 a.m.