Triple

T3224254
Position Surface form Disambiguated ID Type / Status
Subject National Capital Region E67585 entity
Predicate composedOf P402 FINISHED
Object Caloocan E214542 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: Caloocan | Statement: [National Capital Region, composedOf, Caloocan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caloocan
Context triple: [National Capital Region, composedOf, Caloocan]
  • A. Caloocan chosen
    Caloocan is a highly urbanized city in the Philippines that forms part of the northern section of Metro Manila and serves as a major residential and commercial hub.
  • B. Cavite City
    Cavite City is a coastal urban center in the province of Cavite in the Philippines, historically significant as a former Spanish colonial port and naval base near Metro Manila.
  • C. Muntinlupa
    Muntinlupa is a highly urbanized city in the southern part of Metro Manila in the Philippines, known for housing the New Bilibid Prison and major commercial and residential developments like Alabang.
  • D. Mandaluyong
    Mandaluyong is a highly urbanized city in the Philippines known as part of Metro Manila’s central business and commercial district.
  • E. Quezon City
    Quezon City is a major urban center in Metro Manila known for hosting many national government institutions, universities, and media networks in the Philippines.
  • 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_69ad858b8adc8190ad989712c87a476b completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adae1ae8f08190880d0f0e8539cdbc completed March 8, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28e9479fc819092442f50d0b883f8 completed March 12, 2026, 9:59 a.m.
Created at: March 8, 2026, 3:08 p.m.