Triple

T18002134
Position Surface form Disambiguated ID Type / Status
Subject Barangay Kapitolyo E430653 entity
Predicate locatedIn P40 FINISHED
Object Pasig 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: Pasig | Statement: [Barangay Kapitolyo, locatedIn, Pasig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pasig
Context triple: [Barangay Kapitolyo, locatedIn, 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. Lungsod ng Pasig
    Lungsod ng Pasig is a highly urbanized city in Metro Manila, Philippines, known as a major commercial and residential center that includes the Ortigas Center business district.
  • E. Marikina Valley
    Marikina Valley is a low-lying alluvial valley in the eastern part of Metro Manila, Philippines, known for its dense urban communities and susceptibility to flooding from the Marikina River.
  • 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_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b3e9498c8190bdfa7a53b0c0d8db completed April 19, 2026, 10:52 a.m.
Created at: April 10, 2026, 10:23 a.m.