Triple
T13821444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Possenhofen station |
E332143
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Possenhofen |
E235838
|
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: Possenhofen | Statement: [Possenhofen station, adjacentTo, Possenhofen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Possenhofen Context triple: [Possenhofen station, adjacentTo, Possenhofen]
-
A.
Possenhofen
chosen
Possenhofen is a lakeside village in Bavaria, Germany, best known for its historic castle and its association with Empress Elisabeth of Austria ("Sisi").
-
B.
Zusenhofen
Zusenhofen is a village and district within the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
C.
Gersthofen
Gersthofen is a town in Bavaria, Germany, located just north of Augsburg and known for its industrial presence and role as a regional transport hub.
-
D.
Pfeffenhausen
Pfeffenhausen is a market town in Lower Bavaria, Germany, known for its rural character and location within the Landshut district.
-
E.
Vilgertshofen
Vilgertshofen is a small rural municipality in the Bavarian region of Germany, characterized by its agricultural landscape and village-style community.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0284428081908043c55caeefb833 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2189c1cc819080dc296b17e42374 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 9, 2026, 10:12 p.m.