Triple
T23247261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forchtenberg |
E581613
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Öhringen |
—
|
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: Öhringen | Statement: [Forchtenberg, locatedNear, Öhringen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Öhringen Context triple: [Forchtenberg, locatedNear, Öhringen]
-
A.
Öhringen
chosen
Öhringen is a historic town in the German state of Baden-Württemberg, known for its medieval architecture and role as an economic and cultural center in the Hohenlohe region.
-
B.
Wehringen
Wehringen is a small municipality in Bavaria, Germany, situated in the region surrounding the city of Augsburg.
-
C.
Bötzingen
Bötzingen is a municipality in southwestern Germany’s Baden-Württemberg region, situated near Freiburg in the Breisgau wine-growing area.
-
D.
Oberkochen
Oberkochen is a small town in the German state of Baden-Württemberg, known especially as the headquarters of the optics company Carl Zeiss.
-
E.
Schorndorf
Schorndorf is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval center and as the birthplace of automotive pioneer Gottlieb Daimler.
- 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_69e24606b17c81908aba1a4911c8a8ba |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f193f1e8448190b8420a8dc6e24576 |
completed | April 29, 2026, 5:15 a.m. |
Created at: April 17, 2026, 4:10 p.m.