Triple
T13440950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elbingerode (Harz) |
E320357
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Rübeland |
E328446
|
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: Rübeland | Statement: [Elbingerode (Harz), locatedNear, Rübeland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rübeland Context triple: [Elbingerode (Harz), locatedNear, Rübeland]
-
A.
Rübeland
chosen
Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
-
B.
Löwenberger Land
Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
-
C.
Schwanfeld
Schwanfeld is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and historical roots.
-
D.
Kellerwald
Kellerwald is a low mountain forest region in central Germany known for its ancient beech woodlands and protected national park status.
-
E.
Flachsland
Flachsland is a German-language surname associated with individuals such as Maria Karoline Flachsland.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee704ac8190b4c7f4e0d3a88494 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f74621474c8190b96a8f8561451bed |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:40 p.m.