Triple
T20917009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-chanf |
E515097
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object | Bever |
—
|
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: Bever | Statement: [S-chanf, neighboringMunicipality, Bever]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bever Context triple: [S-chanf, neighboringMunicipality, Bever]
-
A.
Bever
Bever is a small river in Germany that serves as one of the tributaries feeding into the Weser.
-
B.
Bever
chosen
Bever is a small Swiss alpine village and municipality in the canton of Graubünden, known for its traditional Engadine architecture and scenic mountain surroundings.
-
C.
Bevin
Bevin is a surname most notably associated with Ernest Bevin, a prominent British Labour politician and post–World War II Foreign Secretary.
-
D.
Bever Dam
Bever Dam is one of the German dams targeted by the RAF's famous World War II "Dambusters" bombing raid in 1943.
-
E.
Beverle
Beverle "Bebe" Buell is an American model, singer, and former fashion icon known for her work in the 1970s and her connections to prominent rock musicians.
- 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec635f4881909a560fb891100d8c |
completed | April 21, 2026, 3:17 a.m. |
Created at: April 16, 2026, 12:48 p.m.