Triple
T8715031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munich U-Bahn lines U3 and U6 |
E206871
|
entity |
| Predicate | fareZoneSystem |
P395
|
FINISHED |
| Object |
MVV zones
MVV zones are the structured public transport fare areas used in the Munich metropolitan region’s integrated transit network.
|
E753890
|
NE FINISHED |
How this triple was built (4 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: MVV zones | Statement: [Munich U-Bahn lines U3 and U6, fareZoneSystem, MVV zones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MVV zones Context triple: [Munich U-Bahn lines U3 and U6, fareZoneSystem, MVV zones]
-
A.
Breng zone Nijmegen
Breng zone Nijmegen is a public transport fare zone in and around the Dutch city of Nijmegen used for regional bus and train ticketing.
-
B.
PVV
PVV is a Dutch right-wing populist political party led by Geert Wilders, known for its anti-immigration and Eurosceptic positions.
-
C.
ZVV
ZVV is the Zürcher Verkehrsverbund, the integrated public transport network and fare association for the Zurich metropolitan area in Switzerland.
-
D.
Zoetermeer Oost
Zoetermeer Oost is a railway station serving the eastern part of the city of Zoetermeer in the Netherlands.
-
E.
Stadionbuurt
Stadionbuurt is a residential neighborhood in Amsterdam, Netherlands, known for its early 20th-century urban design and proximity to the Olympic Stadium.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MVV zones Triple: [Munich U-Bahn lines U3 and U6, fareZoneSystem, MVV zones]
Generated description
MVV zones are the structured public transport fare areas used in the Munich metropolitan region’s integrated transit network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MVV zones Target entity description: MVV zones are the structured public transport fare areas used in the Munich metropolitan region’s integrated transit network.
-
A.
Breng zone Nijmegen
Breng zone Nijmegen is a public transport fare zone in and around the Dutch city of Nijmegen used for regional bus and train ticketing.
-
B.
PVV
PVV is a Dutch right-wing populist political party led by Geert Wilders, known for its anti-immigration and Eurosceptic positions.
-
C.
ZVV
ZVV is the Zürcher Verkehrsverbund, the integrated public transport network and fare association for the Zurich metropolitan area in Switzerland.
-
D.
Zoetermeer Oost
Zoetermeer Oost is a railway station serving the eastern part of the city of Zoetermeer in the Netherlands.
-
E.
Stadionbuurt
Stadionbuurt is a residential neighborhood in Amsterdam, Netherlands, known for its early 20th-century urban design and proximity to the Olympic Stadium.
- F. None of above. chosen
Provenance (5 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd6707c819092c9fca34f273d5e |
completed | March 31, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf28d62af88190acf2d8692d73b9f5 |
completed | April 3, 2026, 2:41 a.m. |
| NEDg | Description generation | batch_69cf2bd222b08190907ba7e98991996e |
completed | April 3, 2026, 2:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf2fcb5e7c819086b441d1ef4fc368 |
completed | April 3, 2026, 3:11 a.m. |
Created at: March 30, 2026, 6:35 p.m.