Triple
T7293116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mödling |
E164446
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Bitterfeld-Wolfen |
E118183
|
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: Bitterfeld-Wolfen | Statement: [Mödling, hasTwinTown, Bitterfeld-Wolfen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bitterfeld-Wolfen Context triple: [Mödling, hasTwinTown, Bitterfeld-Wolfen]
-
A.
Bitterfeld-Wolfen
chosen
Bitterfeld-Wolfen is a town in Saxony-Anhalt, Germany, known for its industrial heritage, particularly in chemical production and film manufacturing.
-
B.
Oschersleben
Oschersleben is a town in the German state of Saxony-Anhalt, known for its motorsport race track Motorsport Arena Oschersleben.
-
C.
Haldensleben
Haldensleben is a town in the German state of Saxony-Anhalt, known as an administrative and economic center with historical roots dating back to the Middle Ages.
-
D.
Zerbst
Zerbst is a historic town in Saxony-Anhalt, Germany, known as the birthplace of Catherine the Great and for its former role as a princely residence.
-
E.
Bernburg
Bernburg is a town in the German state of Saxony-Anhalt, historically known for its castle overlooking the Saale River and its role as an industrial and cultural center in the region.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb6fc5788190b1b339d051f93c22 |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e53faa0481909758a7366cbbe99f |
completed | March 28, 2026, 2:27 p.m. |
Created at: March 27, 2026, 3 p.m.