Triple
T22383625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siebengebirge |
E553337
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Petersberg |
E855158
|
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: Petersberg | Statement: [Siebengebirge, contains, Petersberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Petersberg Context triple: [Siebengebirge, contains, Petersberg]
-
A.
Petersberg
Petersberg is a municipality in the Saalekreis district of Saxony-Anhalt, Germany, known for its rural character and proximity to the city of Halle (Saale).
-
B.
Petersberg
chosen
Petersberg is a hill near Bonn in Germany best known for its historic grand hotel that has hosted numerous high-profile political events and conferences.
-
C.
La Hague
La Hague is a coastal commune in northwestern France known for its rugged cliffs, scenic landscapes, and proximity to major nuclear reprocessing facilities.
-
D.
Eidsberg
Eidsberg is a former municipality and rural town area in southeastern Norway, historically part of Østfold county and known for its agricultural landscape and cultural heritage.
-
E.
Cölln
Cölln was a historic town on the River Spree that, together with Berlin, formed the core of what later became the city of Berlin.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1582d8e548190a7330de49d519675 |
completed | April 29, 2026, 1 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae9b5fccc8190acc5ea778e19f7d5 |
completed | May 18, 2026, 10:28 a.m. |
Created at: April 16, 2026, 8:45 p.m.