Triple

T20025941
Position Surface form Disambiguated ID Type / Status
Subject Puka Shell Beach E494980 entity
Predicate province P604 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: [Puka Shell Beach, province, Aklan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aklan
Context triple: [Puka Shell Beach, province, 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. Province of Aklan
    The Province of Aklan is a coastal province in the Western Visayas region of the Philippines, best known as the gateway to the popular island destination of Boracay.
  • D. Aklanon
    Aklanon is an Austronesian language spoken primarily in the province of Aklan in the central Philippines.
  • E. Apayao
    Apayao is a landlocked, mountainous province in the northern Philippines known for its rich indigenous culture, forests, and river systems.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6628d5b8c8190a35f95ac4a016550 completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:35 p.m.