Triple
T14330193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Audi Q4 e-tron |
E355324
|
entity |
| Predicate | assemblyLocation |
P40
|
FINISHED |
| Object | Zwickau, Germany |
E102035
|
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: Zwickau, Germany | Statement: [Audi Q4 e-tron, assemblyLocation, Zwickau, Germany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zwickau, Germany Context triple: [Audi Q4 e-tron, assemblyLocation, Zwickau, Germany]
-
A.
Zwickau
chosen
Zwickau is a city in the German state of Saxony known historically as an important center of the automotive industry and as the birthplace of composer Robert Schumann.
-
B.
Deggendorf, Germany
Deggendorf, Germany is a Bavarian town on the Danube River known as a regional commercial and industrial center with strong ties to manufacturing and technology companies.
-
C.
Döberitz, Germany
Döberitz, Germany is a locality historically known for its military airfield and role in early German aviation testing and development.
-
D.
Weingarten, Germany
Weingarten, Germany is a town in the state of Baden-Württemberg known for its historic basilica and cultural traditions.
-
E.
Frohnhausen, Germany
Frohnhausen is a district in Germany known in part for its town-twinning partnership with Much Wenlock in England.
- 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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c1def0081908f03cda8e84d20c0 |
completed | April 14, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46943dac819092f5935d9d312949 |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:13 a.m.