Triple
T12617971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulm–Oberstdorf railway |
E301301
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Immenstadt |
E780027
|
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: Immenstadt | Statement: [Ulm–Oberstdorf railway, passesThrough, Immenstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Immenstadt Context triple: [Ulm–Oberstdorf railway, passesThrough, Immenstadt]
-
A.
Immenstadt im Allgäu
chosen
Immenstadt im Allgäu is a Bavarian town in southern Germany known for its scenic location in the Allgäu Alps and its appeal as a regional tourism and outdoor recreation center.
-
B.
Kunreuth
Kunreuth is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and historic castle.
-
C.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
-
D.
Miesbach
Miesbach is a historic town in southern Germany known for its traditional Bavarian culture and picturesque Alpine foothill setting.
-
E.
Schwanau
Schwanau is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine River and the French border.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d960c63ea48190ae1aae9280a023a6 |
completed | April 10, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76b9383088190a0194cd0e666d11c |
completed | May 3, 2026, 3:36 p.m. |
Created at: April 9, 2026, 5:13 p.m.