Triple
T12158223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wurzen |
E289633
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Burkartshain |
E842727
|
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: Burkartshain | Statement: [Wurzen, hasSubdivision, Burkartshain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burkartshain Context triple: [Wurzen, hasSubdivision, Burkartshain]
-
A.
Belgershain
chosen
Belgershain is a small municipality in the Leipzig district of Saxony, Germany, situated southeast of the city of Leipzig.
-
B.
Blatzheim
Blatzheim is a village and district within the town of Kerpen in North Rhine-Westphalia, Germany.
-
C.
Barnacken
Barnacken is a hill in North Rhine-Westphalia, Germany, known as the highest elevation in the Teutoburg Forest range.
-
D.
Braunshardt
Braunshardt is a district of the town of Weiterstadt in the state of Hesse, Germany.
-
E.
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915c277e481908351bf4e664dda42 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f69e8498819080d571e6fb4edfde |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.