Triple
T724037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FÜ |
E14681
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Fürth, Bavaria |
E2619
|
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: Fürth, Bavaria | Statement: [FÜ, region, Fürth, Bavaria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fürth, Bavaria Context triple: [FÜ, region, Fürth, Bavaria]
-
A.
Fürth, Bavaria, Germany
chosen
Fürth is a historic city in the German state of Bavaria, now part of the Nuremberg metropolitan area and known for its rich cultural heritage and Jewish history.
-
B.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
C.
Bavaria
Bavaria is a historic region and federal state in southeastern Germany, known for its distinct cultural traditions, large size and population, and major cities such as Munich.
-
D.
Herzogenaurach, Germany
Herzogenaurach, Germany is a Bavarian town internationally known as the home base of major sportswear companies Adidas and Puma.
-
E.
Swabia (Bavaria)
Swabia (Bavaria) is an administrative region in southwestern Bavaria, Germany, known for its distinct Swabian cultural heritage and mix of industrial cities 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5a6ab508190b70a05a9d77829a5 |
completed | March 1, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a9338feedc8190bc5f489428babd82 |
completed | March 5, 2026, 7:41 a.m. |
Created at: March 1, 2026, 7:37 p.m.