Triple

T16360752
Position Surface form Disambiguated ID Type / Status
Subject Norzagaray E397302 entity
Predicate provinceCapital P16248 FINISHED
Object Malolos E385995 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: Malolos | Statement: [Norzagaray, provinceCapital, Malolos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malolos
Context triple: [Norzagaray, provinceCapital, Malolos]
  • A. Malolos chosen
    Malolos is a historic city in the Philippines best known as the birthplace of the First Philippine Republic and the site of the Malolos Congress.
  • B. Paete
    Paete is a lakeside municipality in the Philippine province of Laguna renowned for its skilled woodcarving and papier-mâché artisans.
  • C. Sta. Cruz
    Sta. Cruz is a coastal municipality in the province of Zambales in the Philippines, known for its fishing communities and proximity to the West Philippine Sea.
  • D. Sta. Cruz
    Sta. Cruz is a coastal municipality in the province of Ilocos Sur in the Philippines, known for its agricultural economy and proximity to the South China Sea.
  • E. Dasmariñas
    Dasmariñas is a rapidly urbanizing city in the province of Cavite in the Philippines, known as a major residential, commercial, and educational hub south of Metro Manila.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2fad304448190b3f6f0350a1e151d completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ecdffac81908ca03a88974203f9 completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:08 a.m.