Triple
T16792409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuremberg–Regensburg railway |
E408141
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Beratzhausen |
E899488
|
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: Beratzhausen | Statement: [Nuremberg–Regensburg railway, passesThrough, Beratzhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beratzhausen Context triple: [Nuremberg–Regensburg railway, passesThrough, Beratzhausen]
-
A.
Beratzhausen
chosen
Beratzhausen is a market town in the Upper Palatinate region of Bavaria, Germany, known for its historic center and location in the scenic Laber valley.
-
B.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
C.
Tussenhausen
Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
-
D.
Hagsdorf
Hagsdorf is a small locality that forms part of the municipality of Persenbeug-Gottsdorf in Lower Austria.
-
E.
Hettenshausen
Hettenshausen is a municipality in the district of Pfaffenhofen an der Ilm in Bavaria, Germany.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a6c9888190b3f8f625b299574d |
completed | April 18, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170dd38708190b17cee0ab6cee6eb |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:22 a.m.