Triple
T15722070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suhl |
E381119
|
entity |
| Predicate | nearbyMountain |
P10602
|
FINISHED |
| Object | Großer Beerberg |
E851151
|
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 Beerberg | Statement: [Suhl, nearbyMountain, Großer Beerberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Großer Beerberg Context triple: [Suhl, nearbyMountain, Großer Beerberg]
-
A.
Großer Beerberg
chosen
Großer Beerberg is a prominent mountain in central Germany known as the highest peak of the Thuringian Forest range.
-
B.
Rüdesheimer Berg
Rüdesheimer Berg is a renowned steep vineyard site in Germany’s Rheingau wine region, famous for producing high-quality Riesling wines.
-
C.
Witzmannsberg
Witzmannsberg is a small rural municipality in the Bavarian region of Lower Bavaria, Germany, known for its scenic countryside and traditional village character.
-
D.
Rohrbach-Berg
Rohrbach-Berg is a small market town in Upper Austria that serves as an important local hub for administration, commerce, and services in the Mühlviertel region.
-
E.
Wackersberg
Wackersberg is a rural Bavarian municipality in southern Germany, known for its scenic Alpine foothills and traditional village character.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb0b51081908e652ec4992296fa |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82f464008190ae0e79f50b9b3eb3 |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 4:45 a.m.