Triple
T13048623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirador station |
E327390
|
entity |
| Predicate | line |
P1293
|
FINISHED |
| Object | Line 5 |
E452470
|
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: Line 5 | Statement: [Mirador station, line, Line 5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 5 Context triple: [Mirador station, line, Line 5]
-
A.
Line 5
Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
-
B.
Line 5
Line 5 is a planned light rail transit line in Toronto’s Eglinton Avenue corridor that will form part of the city’s rapid transit network.
-
C.
Line 5
Line 5 is a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
-
D.
Line 5
Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
-
E.
Line 5
chosen
Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980b8811c81908577f092e2736610 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd8f1308190992c0bd832e1b05e |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:57 p.m.