Triple

T4335016
Position Surface form Disambiguated ID Type / Status
Subject Calabarzon E97442 entity
Predicate hasCity P316 FINISHED
Object Dasmariñas E205490 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: Dasmariñas | Statement: [Calabarzon, hasCity, Dasmariñas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dasmariñas
Context triple: [Calabarzon, hasCity, Dasmariñas]
  • A. Dasmariñas chosen
    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.
  • B. 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.
  • C. Carmona
    Carmona is a municipality in the province of Cavite in the Philippines, known for its mix of residential communities and industrial estates.
  • 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. San Pedro, Laguna
    San Pedro, Laguna is a suburban city in the province of Laguna, Philippines, situated just south of Metro Manila along the shores of Laguna de Bay.
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35152bfc88190ab5d53ca38f98d8a completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b66b29cbe4819083788fe6e3e8ba3b completed March 15, 2026, 8:17 a.m.
Created at: March 12, 2026, 11:14 p.m.