Triple
T21903948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S3 line |
E540881
|
entity |
| Predicate | network |
P2637
|
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: [S3 line, network, ZVV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ZVV Context triple: [S3 line, network, 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.
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trains in German-speaking countries, known for providing relatively quick intercity connections before being largely superseded by newer service categories.
-
D.
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.
-
E.
HVV
HVV is the Hamburg public transport association that coordinates and operates regional transit services in and around Hamburg, Germany.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f121d3c23081908c30c3a617002389 |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 16, 2026, 7:26 p.m.