Triple

T2369971
Position Surface form Disambiguated ID Type / Status
Subject Pasig River E46063 entity
Predicate cityOnBank P7935 FINISHED
Object Makati E107424 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: Makati | Statement: [Pasig River, cityOnBank, Makati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makati
Context triple: [Pasig River, cityOnBank, Makati]
  • A. Makati chosen
    Makati is a highly urbanized city in Metro Manila, Philippines, known as the country’s leading financial and business center.
  • B. 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.
  • C. Metro Manila
    Metro Manila is the densely populated national capital region of the Philippines, encompassing Manila and several surrounding cities as the country’s political, economic, and cultural center.
  • D. Manila
    Manila is the capital city of the Philippines, a historic and densely populated coastal metropolis that has long served as the country’s political, economic, and cultural center.
  • E. Caloocan
    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.
  • 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abd0d813dc8190aa331cdca0b75eca completed March 7, 2026, 7:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69b108bbc090819092b76eb134aad909 completed March 11, 2026, 6:16 a.m.
Created at: March 4, 2026, 7:56 p.m.