Triple

T2542184
Position Surface form Disambiguated ID Type / Status
Subject LRT Line 2 E57808 entity
Predicate hasStation P35 FINISHED
Object Antipolo station E279094 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: Antipolo station | Statement: [LRT Line 2, hasStation, Antipolo station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antipolo station
Context triple: [LRT Line 2, hasStation, Antipolo station]
  • A. Antipolo station chosen
    Antipolo station is an elevated eastern terminal station of Manila’s LRT Line 2 serving the city of Antipolo in Rizal, Philippines.
  • B. Marikina–Pasig station
    Marikina–Pasig station is an elevated rail station in Metro Manila, Philippines, serving commuters in the cities of Marikina and Pasig along the LRT Line 2 corridor.
  • C. Katipunan station
    Katipunan station is an elevated rapid transit stop in Quezon City, Philippines, serving the Katipunan Avenue area and nearby universities on Manila’s LRT Line 2.
  • D. Sagrado Corazón station
    Sagrado Corazón station is a major rapid transit station in San Juan, Puerto Rico, serving as the northern endpoint of the city's Tren Urbano metro system.
  • E. Betty Go-Belmonte station
    Betty Go-Belmonte station is an elevated light rail transit station in Quezon City, Philippines, serving commuters along Manila's LRT Line 2.
  • 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_69ab4a5212d88190b989ce129f2ad87f completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd2bd92f88190bf100c799f62210c completed March 7, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98ab023481908ab51febe79b963c completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:47 p.m.