Triple
T2025190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Bavaria |
E44191
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Fürstenfeldbruck |
E233084
|
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: Fürstenfeldbruck | Statement: [Upper Bavaria, contains, Fürstenfeldbruck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fürstenfeldbruck Context triple: [Upper Bavaria, contains, Fürstenfeldbruck]
-
A.
Forchheim
Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
-
B.
Landsberg am Lech
Landsberg am Lech is a historic Bavarian town in southern Germany known for its medieval old town, picturesque setting on the Lech River, and its association with the nearby Landsberg Prison.
-
C.
Traunstein
Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
-
D.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
E.
Fürstenfeldbruck district
chosen
Fürstenfeldbruck district is an administrative district in Upper Bavaria, Germany, known for its proximity to Munich and a mix of suburban communities and rural landscapes.
- 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8f3faa08190a48ae1355d6e009f |
completed | March 7, 2026, 5:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38b9e52688190bd9dc7fb17e892f8 |
completed | March 13, 2026, 3:59 a.m. |
Created at: March 4, 2026, 7:38 p.m.