Triple
T19325861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voith-Arena |
E483348
|
entity |
| Predicate | hasAddressLocality |
P7943
|
FINISHED |
| Object | Heidenheim |
—
|
NE NERFINISHED |
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: Heidenheim | Statement: [Voith-Arena, hasAddressLocality, Heidenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heidenheim Context triple: [Voith-Arena, hasAddressLocality, Heidenheim]
-
A.
Heidenheim an der Brenz
chosen
Heidenheim an der Brenz is a town in the German state of Baden-Württemberg known for its industrial heritage, historic castle Hellenstein, and location on the Brenz River near the Swabian Jura.
-
B.
Harzheim
Harzheim is a village in the town of Mechernich in North Rhine-Westphalia, Germany.
-
C.
Tharandt
Tharandt is a small town in the Free State of Saxony, Germany, known for its historic forestry academy and scenic location in the Tharandt Forest near Dresden.
-
D.
Laupheim
Laupheim is a town in the district of Biberach in the German state of Baden-Württemberg, known historically for its Jewish community and as an industrial and cultural center in Upper Swabia.
-
E.
Heidenau
Heidenau is a small town in the German state of Saxony, located near Dresden along the Elbe River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d8bb28c81909b3a3bbb96b69b4f |
completed | April 20, 2026, 11:27 a.m. |
Created at: April 10, 2026, 1:33 p.m.