Triple
T4286743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taunus |
E97286
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object | Hoher Taunus |
E209318
|
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: Hoher Taunus | Statement: [Taunus, hasSubregion, Hoher Taunus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoher Taunus Context triple: [Taunus, hasSubregion, Hoher Taunus]
-
A.
Hochtaunus
chosen
Hochtaunus is a highland area in the central Taunus Mountains of Hesse, Germany, known for its forested hills, scenic landscapes, and popular hiking and recreation opportunities.
-
B.
Eifel Mountains
The Eifel Mountains are a low mountain range in western Germany and eastern Belgium, known for their volcanic landscapes, dense forests, and picturesque villages.
-
C.
Rhön
Rhön is a low mountain range in central Germany known for its volcanic landscape, open plateaus, and designation as a UNESCO Biosphere Reserve.
-
D.
Kyffhäuser hills
The Kyffhäuser hills are a low mountain range in central Germany known for the Kyffhäuser Monument and their association with the Barbarossa legend.
-
E.
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.
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3505d23d88190a638f2cc2acee9ee |
completed | March 12, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7c8c1ac819086ded38c1abe9b63 |
completed | March 14, 2026, 7:32 p.m. |
Created at: March 12, 2026, 11:08 p.m.