Triple
T8797190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Großer Feldberg |
E209317
|
entity |
| Predicate | GermanName |
P6492
|
FINISHED |
| Object | Großer Feldberg |
E209317
|
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: Großer Feldberg | Statement: [Großer Feldberg, GermanName, Großer Feldberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Großer Feldberg Context triple: [Großer Feldberg, GermanName, Großer Feldberg]
-
A.
Großer Feldberg
chosen
Großer Feldberg is a prominent mountain in Hesse, Germany, known for its scenic views, hiking trails, and telecommunications facilities.
-
B.
Witzmannsberg
Witzmannsberg is a small rural municipality in the Bavarian region of Lower Bavaria, Germany, known for its scenic countryside and traditional village character.
-
C.
Bärenkopf
Bärenkopf is a mountain peak in the Austrian Alps that forms part of the Glockner Group.
-
D.
Feldberg
Feldberg is the tallest mountain in Germany’s Black Forest region, known for its scenic landscapes and popular hiking and skiing opportunities.
-
E.
Konradshöhe
Konradshöhe is a leafy, riverside locality in the northwest of Berlin known for its tranquil, village-like character within the borough of Reinickendorf.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa370d08190885ef65e3a3e56d3 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6f5d655881909013ac3e2ac0cebb |
completed | April 3, 2026, 7:42 a.m. |
Created at: March 30, 2026, 6:44 p.m.