Triple
T20644475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esslingen district |
E507315
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bissingen an der Teck |
—
|
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: Bissingen an der Teck | Statement: [Esslingen district, contains, Bissingen an der Teck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bissingen an der Teck Context triple: [Esslingen district, contains, Bissingen an der Teck]
-
A.
Bissingen
Bissingen is a municipality in the Donau-Ries district of Bavaria in southern Germany, known for its rural character and location near the Swabian Jura.
-
B.
Bissingen
chosen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
C.
Weilheim an der Teck
Weilheim an der Teck is a small historic town in the German state of Baden-Württemberg, located at the foot of the Swabian Alps in southern Germany.
-
D.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
E.
Bösingen
Bösingen is a municipality in the canton of Fribourg in western Switzerland, known for its rural character and proximity to the city of Bern.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1d0be481909e090193dcfd9cf6 |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.