Triple

T11679724
Position Surface form Disambiguated ID Type / Status
Subject Manila Light Rail Transit System E277583 entity
Predicate serves P98 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: [Manila Light Rail Transit System, serves, Makati]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makati
Context triple: [Manila Light Rail Transit System, serves, 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 OpenStack shared file system service that provides scalable, API-driven management of networked file shares.
  • E. 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.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a461b0908190bef4e1c6777affcf completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69f72654dc88819095bc1ce23dfee4df completed May 3, 2026, 10:41 a.m.
Created at: April 8, 2026, 9:40 p.m.