Triple

T3212748
Position Surface form Disambiguated ID Type / Status
Subject Bicol Region E67318 entity
Predicate hasProvince P285 FINISHED
Object Albay E340173 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: Albay | Statement: [Bicol Region, hasProvince, Albay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albay
Context triple: [Bicol Region, hasProvince, Albay]
  • A. Albay chosen
    Albay is a province in the Bicol Region of the Philippines, known for the iconic Mayon Volcano and its rich Bikolano culture.
  • B. Marinduque
    Marinduque is an island province in the Philippines known for its heart-shaped geography and the annual Moriones Festival.
  • C. Catanduanes
    Catanduanes is an island province in the Bicol Region of the Philippines known for its rugged coastlines, surfing beaches, and predominantly Bikol-speaking population.
  • D. Siquijor
    Siquijor is a small island province in the central Philippines known for its white-sand beaches, coral reefs, and folklore surrounding mysticism and traditional healing.
  • E. Capiz
    Capiz is a province in the Western Visayas region of the Philippines, known for its coastal landscapes, seafood, and use of the Hiligaynon language.
  • 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_69ad858ac36c81909962589cd277d6e2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaabba8e481909118d9f888ddcd63 completed March 8, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e822b64c8190b053234690841d38 completed March 12, 2026, 4:21 p.m.
Created at: March 8, 2026, 3:07 p.m.