Triple
T12313986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 7-Rubi |
E293551
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Luz station |
E295250
|
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: Luz station | Statement: [Line 7-Rubi, terminus, Luz station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luz station Context triple: [Line 7-Rubi, terminus, Luz station]
-
A.
La Aurora station
La Aurora station is a terminal stop on Medellín’s mass transit system, serving as an endpoint for one of the Metro de Medellín lines.
-
B.
La Raza station
La Raza station is a major Mexico City Metro interchange known for connecting multiple lines and serving as an important transit hub in the city’s northern area.
-
C.
Luz Station
chosen
Luz Station is a historic railway station and major transportation hub in São Paulo, Brazil, known for its distinctive architecture and cultural significance.
-
D.
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.
-
E.
Varela station
Varela station is a stop on Buenos Aires’ Line E subway, serving passengers in the city’s southeastern neighborhoods.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f03d3c88190baedffb83465bff8 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a9d50b081908f0bdb7a2ca2832a |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:53 p.m.