Triple

T5032869
Position Surface form Disambiguated ID Type / Status
Subject Bacolod E113346 entity
Predicate hasSisterCity P919 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: [Bacolod, hasSisterCity, Makati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makati
Context triple: [Bacolod, hasSisterCity, 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. City of Makati
    The City of Makati is a highly urbanized Philippine city in Metro Manila known as the country’s leading financial and central business district.
  • 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_69bd443775e48190a646ffbfc4334723 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73b68d8c8190b8e04fb406abdb0f completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf219bdd208190990db4b0fa89066a completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 1:36 p.m.