Triple

T8181175
Position Surface form Disambiguated ID Type / Status
Subject Subte E191062 entity
Predicate hasStation P35 FINISHED
Object Retiro station E192128 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: Retiro station | Statement: [Subte, hasStation, Retiro station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Retiro station
Context triple: [Subte, hasStation, Retiro station]
  • A. Retiro station chosen
    Retiro station is a major Buenos Aires Underground terminus and transport hub located in the Retiro district of Argentina’s capital.
  • B. Pino Suárez station
    Pino Suárez station is a major Mexico City Metro interchange hub located in the historic center, connecting multiple lines and serving as a key transit point for commuters.
  • C. Francisco station
    Francisco station is an elevated Chicago 'L' rapid transit stop on the Brown Line located in the city's Ravenswood Manor neighborhood.
  • D. 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.
  • E. San Pedrito station
    San Pedrito station is the western terminal of Line A on the Buenos Aires Underground (Subte) system in Argentina.
  • 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_69ca82c4538081909404325aa5639483 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4c4c2e388190b86854f8b1765e61 completed March 31, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd94bbdc288190aee5187e95ca7a8d completed April 1, 2026, 9:57 p.m.
Created at: March 30, 2026, 5:40 p.m.