Triple
T20522478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bern Bümpliz Nord railway station |
E503843
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Bümpliz Nord |
—
|
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: Bümpliz Nord | Statement: [Bern Bümpliz Nord railway station, hasAbbreviation, Bümpliz Nord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bümpliz Nord Context triple: [Bern Bümpliz Nord railway station, hasAbbreviation, Bümpliz Nord]
-
A.
Bümpliz
chosen
Bümpliz is a district of the Swiss city of Bern, known as a largely residential area with local industry and transport facilities.
-
B.
Bösperde
Bösperde is a district of the town of Menden in North Rhine-Westphalia, Germany, known as a primarily residential suburban area.
-
C.
Bumehen
Bumehen is a city in Iran that serves as one of the urban settlements within Pardis County, near Tehran.
-
D.
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.
-
E.
Dhünn
Dhünn is a river in North Rhine-Westphalia, Germany, that flows through the city of Leverkusen and serves as a tributary of the Wupper.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f46488c819093687b4e07837793 |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.