Triple

T3908631
Position Surface form Disambiguated ID Type / Status
Subject Bulacan E87267 entity
Predicate capital P234 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: [Bulacan, capital, Malolos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malolos
Context triple: [Bulacan, capital, 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. 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.
  • C. Canlaon
    Canlaon is a city in the Philippines known for its proximity to Mount Kanlaon, an active volcano and prominent natural landmark on Negros Island.
  • D. Las Piñas
    Las Piñas is a highly urbanized city in the southern part of Metro Manila in the Philippines, known for its residential communities and the historic Bamboo Organ.
  • E. Carmona
    Carmona is a municipality in the province of Cavite in the Philippines, known for its mix of residential communities and industrial estates.
  • 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_69aed9424514819086e9c58adde6652d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeed13bb14819096842c6c82342524 completed March 9, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51caf41c881909c5156480b46e794 completed March 14, 2026, 8:30 a.m.
Created at: March 9, 2026, 3:22 p.m.