Triple

T17222342
Position Surface form Disambiguated ID Type / Status
Subject Third District of Nueva Ecija E418016 entity
Predicate hasPart P35 FINISHED
Object Cabanatuan 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: Cabanatuan | Statement: [Third District of Nueva Ecija, hasPart, Cabanatuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cabanatuan
Context triple: [Third District of Nueva Ecija, hasPart, Cabanatuan]
  • A. Cabanatuan City chosen
    Cabanatuan City is a highly urbanized commercial and transportation hub in the Philippine province of Nueva Ecija, historically known as the "Tricycle Capital of the Philippines."
  • B. Dipaculao
    Dipaculao is a coastal municipality in the Philippine province of Aurora known for its beaches, surfing spots, and scenic mountain landscapes.
  • C. Calasiao
    Calasiao is a municipality in the Philippine province of Pangasinan known for its historic churches and famous native rice cakes called "puto Calasiao."
  • D. Tayug
    Tayug is a landlocked agricultural municipality in the province of Pangasinan in the Philippines, known for its rice farming and rural community life.
  • E. Tarlac
    Tarlac is a landlocked province in the Central Luzon region of the Philippines known for its culturally diverse population and agricultural economy.
  • 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_69d886d779488190b131369541c04e7d completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42ddf2c3c8190b6adceaaefd4ccbf completed April 19, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:38 a.m.