Triple
T22354548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S10 line |
E552617
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object | ZVV |
—
|
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: ZVV | Statement: [S10 line, fareSystem, ZVV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ZVV Context triple: [S10 line, fareSystem, ZVV]
-
A.
ZVV
chosen
ZVV is the Zürcher Verkehrsverbund, the integrated public transport network and fare association for the Zurich metropolitan area in Switzerland.
-
B.
ZVVZ
ZVVZ is a Czech industrial company known for producing air-handling, filtration, and environmental technology equipment.
-
C.
ZVV integrated fare network
The ZVV integrated fare network is a unified public transport tariff system covering trains, trams, buses, and other services across the Zurich region, allowing seamless travel with a single ticket.
-
D.
D-Zug
D-Zug was a former class of fast long-distance passenger trains in German-speaking countries, known for providing relatively quick intercity connections before being largely superseded by newer service categories.
-
E.
EV Zug
EV Zug is a professional ice hockey club from Zug, Switzerland, known as one of the prominent teams in the country’s top-tier league.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157ceb2308190941f6507e605a612 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 16, 2026, 8:44 p.m.