Triple
T15864471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zwickau district |
E384673
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Werdau |
E432350
|
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: Werdau | Statement: [Zwickau district, contains, Werdau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Werdau Context triple: [Zwickau district, contains, Werdau]
-
A.
Werdau
chosen
Werdau is a town in the Free State of Saxony in eastern Germany, historically known for its textile and engineering industries.
-
B.
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.
-
C.
Borgholzhausen
Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
-
D.
Crimmitschau
Crimmitschau is a town in the German state of Saxony, historically known for its textile industry and located within the broader Leipzig metropolitan area.
-
E.
Suhl
Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1555e4ee48190a3b27b4ab9bdb1c8 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084a6d6308190ad57a51b380171a2 |
completed | May 10, 2026, 1:14 p.m. |
Created at: April 10, 2026, 4:50 a.m.