Triple

T14633577
Position Surface form Disambiguated ID Type / Status
Subject Cabucgayan E343543 entity
Predicate island P970 FINISHED
Object Biliran Island 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: Biliran Island | Statement: [Cabucgayan, island, Biliran Island]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biliran Island
Context triple: [Cabucgayan, island, Biliran Island]
  • A. Biliran Island chosen
    Biliran Island is a small island province in the Eastern Visayas region of the Philippines known for its coastal landscapes, waterfalls, and predominantly Waray-speaking population.
  • B. Boang Island
    Boang Island is one of the main islands in the Tanga Islands archipelago of Papua New Guinea, known for its small coastal communities and tropical marine environment.
  • C. Siau Island
    Siau Island is a volcanic island in North Sulawesi, Indonesia, known for its active Mount Karangetang and as a major center of the Sitaro Islands Regency.
  • D. Bunguran Island
    Bunguran Island is the largest and most populous island of Indonesia’s Natuna archipelago in the South China Sea.
  • E. Tulang Island
    Tulang Island is a small, scenic island barangay off the coast of San Francisco in Cebu, Philippines, known for its white-sand beaches and clear waters.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4aa7cb48190b008bd6b0e162c89 completed April 14, 2026, 9:42 p.m.
Created at: April 10, 2026, 1:26 a.m.