Triple
T14831776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Nikolaus Church |
E348722
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Rosenheim |
E69439
|
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: Rosenheim | Statement: [St Nikolaus Church, locatedIn, Rosenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosenheim Context triple: [St Nikolaus Church, locatedIn, Rosenheim]
-
A.
Rosenheim
chosen
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
B.
Traunstein
Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
-
C.
Eichstätt
Eichstätt is a historic Bavarian town in southern Germany known for its baroque architecture, Catholic university, and location within the Altmühltal Nature Park.
-
D.
Kempten
Kempten is a historic town in Bavaria, Germany, considered one of the country’s oldest urban settlements and known for its location in the Allgäu region.
-
E.
Kaufbeuren
Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded0748eec8190a39c94024c3a3e3e |
completed | April 14, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a1d8e088190a2168952ab5dc687 |
completed | May 10, 2026, 1:37 p.m. |
Created at: April 10, 2026, 1:52 a.m.