Triple

T18736634
Position Surface form Disambiguated ID Type / Status
Subject Calabarzon E458179 entity
Predicate capital P234 FINISHED
Object Calamba 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: Calamba | Statement: [Calabarzon, capital, Calamba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calamba
Context triple: [Calabarzon, capital, Calamba]
  • A. Calamba City chosen
    Calamba City is a highly urbanized city in the province of Laguna, Philippines, known as the hometown of national hero José Rizal and a major industrial and residential hub south of Metro Manila.
  • B. Abucay
    Abucay is a coastal municipality in the province of Bataan in the Philippines, known for its historical significance dating back to the Spanish colonial period.
  • C. Galapagar
    Galapagar is a municipality in the Community of Madrid, Spain, known for its natural surroundings in the Sierra de Guadarrama and its role as a residential town near the capital.
  • D. Calasiao
    Calasiao is a municipality in the Philippine province of Pangasinan known for its historic churches and famous native rice cakes called "puto Calasiao."
  • E. Batangas City
    Batangas City is a major port and industrial hub in the province of Batangas in the Philippines, known for its oil refineries, commercial activity, and role as a gateway to nearby islands.
  • 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e57689fa508190ad821d361cba9edf completed April 20, 2026, 12:42 a.m.
Created at: April 10, 2026, 11:51 a.m.