Triple
T3966019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-Bahn Nuremberg |
E92218
|
entity |
| Predicate | serves |
P98
|
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: [S-Bahn Nuremberg, serves, Forchheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Forchheim Context triple: [S-Bahn Nuremberg, serves, 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.
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.
-
C.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
D.
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.
-
E.
Kulmbach
Kulmbach is a historic Bavarian town in northern Germany renowned for its beer brewing tradition and its hilltop Plassenburg Castle.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef976f4fc8190b2c16ab62c19cdb8 |
completed | March 9, 2026, 4:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfd70b4a7c8190852503f31142562e |
completed | March 22, 2026, 11:48 a.m. |
Created at: March 9, 2026, 3:32 p.m.