Triple
T15719306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uetliberg railway line |
E381046
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Zürich Binz |
E1200955
|
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: Zürich Binz | Statement: [Uetliberg railway line, hasStation, Zürich Binz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zürich Binz Context triple: [Uetliberg railway line, hasStation, Zürich Binz]
-
A.
Zollikon
Zollikon is an affluent suburban municipality on the shores of Lake Zurich, known for its residential character and proximity to the city of Zurich in Switzerland.
-
B.
Kloten
Kloten is a town in the canton of Zurich in northern Switzerland, best known as the home of Zurich Airport.
-
C.
Regensdorf
Regensdorf is a municipality in the canton of Zürich in northern Switzerland, known as a suburban residential and industrial area near the city of Zürich.
-
D.
Grenchen
Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
-
E.
Zürich Giesshübel
chosen
Zürich Giesshübel is a local railway station in the city of Zurich, Switzerland, serving regional commuter traffic on the Uetliberg line.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f932a248190b65ecfb2bc56e715 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000ec1091c8190a8e4c4db6180129a |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 4:45 a.m.