Triple
T21052236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lima Metro Line 1 |
E518615
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | La Cultura station |
—
|
NE NERFINISHED |
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: La Cultura station | Statement: [Lima Metro Line 1, hasStation, La Cultura station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Cultura station Context triple: [Lima Metro Line 1, hasStation, La Cultura station]
-
A.
La Cultura station
chosen
La Cultura station is a stop on Line 1 of the Lima Metro serving the La Victoria/San Borja area of Lima, Peru.
-
B.
Loria station
Loria station is a stop on Buenos Aires’ Line A subway, serving passengers in the Balvanera neighborhood of the city.
-
C.
Múzquiz station
Múzquiz station is a Mexico City Metro station serving passengers on Line B in the northeastern part of the metropolitan area.
-
D.
Aventura station
Aventura station is a Brightline intercity rail station in Aventura, Florida, serving as a stop on the higher-speed passenger rail line connecting Miami and Orlando.
-
E.
Steinberg Station
Steinberg Station is a local railway stop serving the community of Steinberg and connecting it to the surrounding region’s rail network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7cabe881909e6b258a14d501a6 |
completed | April 21, 2026, 4:30 a.m. |
Created at: April 16, 2026, 2:35 p.m.