Triple
T1730472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volkswagen Golf |
E37797
|
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: [Volkswagen Golf, assemblyLocation, Zwickau, Germany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zwickau, Germany Context triple: [Volkswagen Golf, 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.
Schröttinghausen, Germany
Schröttinghausen is a small locality in Germany best known as the birthplace of influential astronomer Walter Baade.
-
D.
Torgau, Germany
Torgau, Germany is a historic town in Saxony on the Elbe River, known for its Renaissance architecture and its role as a key site in the Protestant Reformation.
-
E.
Chemnitz
Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
- 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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa637f202c8190b46a31bef51465c8 |
completed | March 6, 2026, 5:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8af9c15c8190818a891f5eae6569 |
completed | March 8, 2026, 2:43 p.m. |
Created at: March 4, 2026, 7:30 p.m.