Triple

T4335126
Position Surface form Disambiguated ID Type / Status
Subject Mayon Volcano E97444 entity
Predicate locatedIn P40 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: [Mayon Volcano, locatedIn, Albay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albay
Context triple: [Mayon Volcano, locatedIn, 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35152bfc88190ab5d53ca38f98d8a completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b6134ca4f88190a2aa34bf39d71ac6 completed March 15, 2026, 2:02 a.m.
Created at: March 12, 2026, 11:14 p.m.