Triple
T16424287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyffhäuser hills |
E398897
|
entity |
| Predicate | GermanName |
P6492
|
FINISHED |
| Object | Kyffhäuser |
E398897
|
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: Kyffhäuser | Statement: [Kyffhäuser hills, GermanName, Kyffhäuser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyffhäuser Context triple: [Kyffhäuser hills, GermanName, Kyffhäuser]
-
A.
Kyffhäuser hills
chosen
The Kyffhäuser hills are a low mountain range in central Germany known for the Kyffhäuser Monument and their association with the Barbarossa legend.
-
B.
Rhön
Rhön is a low mountain range in central Germany known for its volcanic landscape, open plateaus, and designation as a UNESCO Biosphere Reserve.
-
C.
Vogelsberg
Vogelsberg is a large volcanic mountain range in the German state of Hesse, known for its forested highlands and rural landscapes.
-
D.
Hardtberg
Hardtberg is a borough of the German city of Bonn, located in the western part of the city and comprising several residential and administrative districts.
-
E.
Fichtelgebirge
Fichtelgebirge is a low mountain range in northeastern Bavaria, Germany, known for its forested granite peaks and as the source region of several major rivers.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328f9da9081908dadbdac4b2d38ec |
completed | April 18, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c70aaa08190bf88210c0b491fc1 |
completed | May 10, 2026, 8:06 a.m. |
Created at: April 10, 2026, 5:09 a.m.