Triple
T17975761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pío Nono station |
E449464
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Zoo 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: Zoo station | Statement: [Pío Nono station, connectsTo, Zoo station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zoo station Context triple: [Pío Nono station, connectsTo, Zoo station]
-
A.
Zoológico station
Zoológico station is a stop on Santiago’s historic funicular railway that serves visitors to the city’s hilltop zoo and surrounding park areas.
-
B.
Zoológico station
chosen
Zoológico station is a metro station in Caracas, Venezuela, serving as one of the terminal stops on the Caracas Metro system.
-
C.
Zeze Station
Zeze Station is a railway station serving the city of Ōtsu in Shiga Prefecture, Japan.
-
D.
Recreo station
Recreo station is a passenger rail station on the Valparaíso Metro system in Chile, serving the coastal area between Valparaíso and Viña del Mar.
-
E.
Zoologischer Garten station
Zoologischer Garten station is a major transport hub in Berlin that serves both U-Bahn and S-Bahn lines near the Berlin Zoological Garden and the Kurfürstendamm shopping district.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1fee86c8190a9a220b008e78e10 |
completed | April 19, 2026, 10:44 a.m. |
Created at: April 10, 2026, 10:22 a.m.