Triple

T8079334
Position Surface form Disambiguated ID Type / Status
Subject Marinduque E188574 entity
Predicate capital P234 FINISHED
Object Boac E458915 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: Boac | Statement: [Marinduque, capital, Boac]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boac
Context triple: [Marinduque, capital, Boac]
  • A. Boac chosen
    Boac is the capital town and main commercial and administrative center of the island province of Marinduque in the Mimaropa region of the Philippines.
  • B. Guanaja Airport
    Guanaja Airport is a small regional airport serving the island of Guanaja in Honduras’ Bay Islands, providing domestic connections and access for tourists and residents.
  • C. Tamarindo
    Tamarindo is a neighborhood within Havana’s Diez de Octubre municipality, known as a densely populated urban residential area in Cuba’s capital.
  • D. Aguas Buenas
    Aguas Buenas is a mountainous municipality in central Puerto Rico known for its cool climate, caves, and scenic rural landscapes.
  • E. Paipa
    Paipa is a Colombian town in the Boyacá Department known for its thermal springs, tourism, and historical significance in the independence era.
  • 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_69ca82b662e88190b9323daab8c28a21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb40a3f01c819096a2c9d5d5199fe6 completed March 31, 2026, 3:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63f79ac08190af49e77bee67921d completed April 1, 2026, 12:16 a.m.
Created at: March 30, 2026, 5:28 p.m.