Triple

T12155887
Position Surface form Disambiguated ID Type / Status
Subject Cubao MRT station E289573 entity
Predicate serves P98 FINISHED
Object Cubao E56239 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: Cubao | Statement: [Cubao MRT station, serves, Cubao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cubao
Context triple: [Cubao MRT station, serves, Cubao]
  • A. Cubao chosen
    Cubao is a major commercial and transport hub in Quezon City, Metro Manila, known for its shopping centers, bus terminals, and entertainment venues.
  • B. Malabon
    Malabon is a coastal city in the northern part of Metro Manila in the Philippines, known for its historic districts, flood-prone waterways, and distinctive local cuisine.
  • C. Central Bicutan
    Central Bicutan is a barangay (administrative district) located within the city of Taguig in Metro Manila, Philippines.
  • D. Batasan Hills, Quezon City
    Batasan Hills, Quezon City is a residential and government district in Metro Manila best known as the site of the Batasang Pambansa Complex, home of the Philippine House of Representatives.
  • E. Makati Central Business District
    Makati Central Business District is the primary financial and commercial hub of Metro Manila, known for its concentration of corporate headquarters, upscale malls, and high-rise office towers.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c1673c8190830cd15525d16869 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a84236c8190baa383c950d2bd62 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:50 p.m.