Triple

T1666417
Position Surface form Disambiguated ID Type / Status
Subject Metro Manila E36022 entity
Predicate containsCity P294 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: [Metro Manila, containsCity, Makati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makati
Context triple: [Metro Manila, containsCity, 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. Cagayan de Oro
    Cagayan de Oro is a highly urbanized city in Northern Mindanao, Philippines, known as a regional economic hub and gateway to the island’s northern corridor.
  • 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90adc57cc8190b270004c363768e3 completed March 5, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1ac4b9c8190a7d0fa610a77f9c3 completed March 8, 2026, 7:44 p.m.
Created at: March 4, 2026, 7:29 p.m.