Triple
T6431463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zürich tram network |
E129786
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object | Hard tram depot |
E557739
|
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: Hard tram depot | Statement: [Zürich tram network, hasDepot, Hard tram depot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hard tram depot Context triple: [Zürich tram network, hasDepot, Hard tram depot]
-
A.
Hard depot
chosen
Hard depot is a major trolleybus facility in Zürich used for housing, maintaining, and dispatching vehicles on the city’s trolleybus network.
-
B.
Dam tram stop
Dam tram stop is a central Amsterdam tram stop located on Dam Square, serving as a key access point to nearby landmarks and major shopping areas.
-
C.
Vastral Depot
Vastral Depot is a major maintenance and operations facility serving the Ahmedabad Metro system in Ahmedabad, India.
-
D.
Skunk Train depot
The Skunk Train depot is the historic Willits station and departure point for scenic heritage railway excursions through Northern California’s redwood forests.
-
E.
Upper Station
Upper Station is the hilltop terminal of Pittsburgh’s historic Duquesne Incline funicular, serving as its upper boarding and observation point.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0693cadf08190aca84888a3440b3d |
completed | March 22, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640e9ae8481909229bcf6d5e793d3 |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:44 p.m.