Triple
T22887773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonn public transport network |
E567650
|
entity |
| Predicate | connectsArea |
P2564
|
FINISHED |
| Object | Beuel |
—
|
NE NERFINISHED |
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: Beuel | Statement: [Bonn public transport network, connectsArea, Beuel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beuel Context triple: [Bonn public transport network, connectsArea, Beuel]
-
A.
Beuel
chosen
Beuel is a district on the right bank of the Rhine in the German city of Bonn, known for its residential areas and local carnival traditions.
-
B.
Belpberg
Belpberg is a small former municipality in the canton of Bern, Switzerland, situated on a plateau above the Gürbetal valley and known for its rural, scenic landscape.
-
C.
Biesterfeld
Biesterfeld was a historic estate in the Principality of Lippe that served as the ancestral seat of the Lippe-Biesterfeld noble line.
-
D.
Schwanebeck
Schwanebeck is a former municipality in Brandenburg, Germany, that now forms part of the town of Panketal.
-
E.
Beyenburg
Beyenburg is a historic district in the eastern part of Wuppertal, Germany, known for its medieval monastery, reservoir, and well-preserved village character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458a92ec81908fc1cd5f6407d2ab |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17fc2adb4819081bce7e6849ba31a |
completed | April 29, 2026, 3:49 a.m. |
Created at: April 17, 2026, 3:40 p.m.