Triple

T11679674
Position Surface form Disambiguated ID Type / Status
Subject Light Rail Transit Authority E277582 entity
Predicate serves P98 FINISHED
Object Metro Manila E36022 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: Metro Manila | Statement: [Light Rail Transit Authority, serves, Metro Manila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metro Manila
Context triple: [Light Rail Transit Authority, serves, Metro Manila]
  • A. Metro Manila chosen
    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.
  • 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. Manila
    Manila is the OpenStack shared file system service that provides scalable, API-driven management of networked file shares.
  • 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. Makati
    Makati is a highly urbanized city in Metro Manila, Philippines, known as the country’s leading financial and business 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_69ef8201715c819090cbd7c1e3068bdd completed April 27, 2026, 3:34 p.m.
Created at: April 8, 2026, 9:40 p.m.