Triple
T3683097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Südwestsachsen region |
E78156
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Zwickau |
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 | Statement: [Südwestsachsen region, contains, Zwickau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zwickau Context triple: [Südwestsachsen region, contains, Zwickau]
-
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.
Chemnitz
Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
-
C.
Zittau
Zittau is a historic town in the southeastern corner of Germany, known for its proximity to both the Czech and Polish borders and its well-preserved medieval architecture.
-
D.
Wurzen
Wurzen is a historic town in the German state of Saxony, known for its medieval architecture and location on the river Mulde east of Leipzig.
-
E.
Werdau
Werdau is a town in the Free State of Saxony in eastern Germany, historically known for its textile and engineering industries.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4948cc48190ab1f59cc4a2437cc |
completed | March 8, 2026, 6:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4d60ae3c8190aea53073a37d0c07 |
completed | March 21, 2026, 7:48 a.m. |
Created at: March 8, 2026, 3:26 p.m.