Triple
T2337382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HH |
E44341
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Hamburg vehicle registration authority |
E7419
|
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: Hamburg vehicle registration authority | Statement: [HH, usedBy, Hamburg vehicle registration authority]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamburg vehicle registration authority Context triple: [HH, usedBy, Hamburg vehicle registration authority]
-
A.
Wolfsburg
Wolfsburg is a German city best known as the headquarters and main production site of the Volkswagen automobile company.
-
B.
Ingolstadt
Ingolstadt is a historic city in southern Germany known for its medieval architecture, university tradition, and role as a major hub of the automotive industry.
-
C.
Hamburg
chosen
Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
-
D.
Bremen
Bremen is a city-state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port on the Weser River.
-
E.
Lüneburg
Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc68ac4348190ab6ec46ec7879643 |
completed | March 7, 2026, 6:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae961adfdc8190bf79d479d8207599 |
completed | March 9, 2026, 9:42 a.m. |
Created at: March 4, 2026, 7:51 p.m.