Triple
T5668543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regnitz |
E124915
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Forchheim |
E248845
|
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: Forchheim | Statement: [Regnitz, flowsThrough, Forchheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Forchheim Context triple: [Regnitz, flowsThrough, Forchheim]
-
A.
Forchheim
chosen
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.
Burghausen
Burghausen is a historic Bavarian town in southeastern Germany, renowned for its remarkably well-preserved medieval old town and one of the longest castle complexes in the world.
-
C.
Aschaffenburg
Aschaffenburg is a historic Bavarian city in Germany known for its riverside setting on the Main, its prominent Schloss Johannisburg castle, and its role as a regional cultural and economic center.
-
D.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
E.
Deggendorf
Deggendorf is a town in southeastern Germany situated on the Danube River, known as a regional commercial and transportation hub near the Bavarian Forest.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c023471f688190acec330596238a50 |
completed | March 22, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c85695cc608190aa6ed016bd3f8929 |
completed | March 28, 2026, 10:30 p.m. |
Created at: March 22, 2026, 3:43 p.m.