Triple
T20811247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ettlingen |
E512308
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Ettlingen-Stadt |
E512308
|
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: Ettlingen-Stadt | Statement: [Ettlingen, hasSubdivision, Ettlingen-Stadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ettlingen-Stadt Context triple: [Ettlingen, hasSubdivision, Ettlingen-Stadt]
-
A.
Ettlingen
chosen
Ettlingen is a historic town in the state of Baden-Württemberg in southwestern Germany, known for its well-preserved old town and proximity to the city of Karlsruhe.
-
B.
Tuttlingen
Tuttlingen is a town in the state of Baden-Württemberg in southern Germany, known as a major center of the medical technology and surgical instrument industry.
-
C.
Ittlingen
Ittlingen is a small municipality in the German state of Baden-Württemberg, located within the Heilbronn region.
-
D.
Bietigheim-Bissingen
Bietigheim-Bissingen is a town in the German state of Baden-Württemberg known for its historic old town, wine-growing tradition, and location near Stuttgart.
-
E.
Schwanstetten
Schwanstetten is a municipality in the Roth district of Bavaria, Germany, known for its residential character and proximity to the city of Nuremberg.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d338ac819096d4a33de831609e |
completed | April 21, 2026, 12:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08f8cb61388190922a898ee4c44d2e |
completed | May 16, 2026, 11:07 p.m. |
Created at: April 16, 2026, 12:40 p.m.