Triple

T2542195
Position Surface form Disambiguated ID Type / Status
Subject LRT Line 2 E57808 entity
Predicate cityServed P82 FINISHED
Object Pasig E97441 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: Pasig | Statement: [LRT Line 2, cityServed, Pasig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pasig
Context triple: [LRT Line 2, cityServed, Pasig]
  • A. Pasig chosen
    Pasig is a highly urbanized city in Metro Manila in the Philippines, known historically as a riverside settlement and now as a major commercial and residential center.
  • B. Marikina
    Marikina is a highly urbanized city in the Philippines known as the "Shoe Capital of the Philippines" for its long-standing shoe-making industry and is part of the Metro Manila region.
  • C. Mandaluyong
    Mandaluyong is a highly urbanized city in the Philippines known as part of Metro Manila’s central business and commercial district.
  • D. Pasig River
    The Pasig River is a historically significant waterway in the Philippines that flows through Metro Manila, linking Laguna de Bay to Manila Bay and serving as a central feature of the capital’s urban landscape.
  • E. 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.
  • 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_69ab4a5212d88190b989ce129f2ad87f completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd2bd92f88190bf100c799f62210c completed March 7, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf3b61fc8190988484bedc5b57a0 completed March 10, 2026, 5:42 a.m.
Created at: March 6, 2026, 9:47 p.m.