Triple

T11679882
Position Surface form Disambiguated ID Type / Status
Subject V. Mapa station E277586 entity
Predicate followedByStation P42146 FINISHED
Object J. Ruiz station E279095 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: J. Ruiz station | Statement: [V. Mapa station, followedByStation, J. Ruiz station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: J. Ruiz station
Context triple: [V. Mapa station, followedByStation, J. Ruiz station]
  • A. J. Ruiz station chosen
    J. Ruiz station is an elevated stop on Manila’s LRT Line 2 serving commuters in the San Juan area of Metro Manila, Philippines.
  • B. Vicente Valdés station
    Vicente Valdés station is a key interchange and terminal station in Santiago's metro network, serving as an important hub for passengers in the southern part of the city.
  • C. Varela station
    Varela station is a stop on Buenos Aires’ Line E subway, serving passengers in the city’s southeastern neighborhoods.
  • D. José María Moreno station
    José María Moreno station is a stop on Buenos Aires’ Line E subway serving the Caballito neighborhood.
  • E. Francisco Goitia station
    Francisco Goitia station is a stop on the Xochimilco Light Rail system in Mexico City, serving local commuters in the southern part of the city.
  • 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_69ef14007dd08190b60640be9949ca26 completed April 27, 2026, 7:45 a.m.
Created at: April 8, 2026, 9:40 p.m.