Triple
T22318335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lovisenberg Diaconal Hospital |
E551708
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Lovisenberg |
—
|
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: Lovisenberg | Statement: [Lovisenberg Diaconal Hospital, locatedIn, Lovisenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lovisenberg Context triple: [Lovisenberg Diaconal Hospital, locatedIn, Lovisenberg]
-
A.
Lovisenberg
chosen
Lovisenberg is a residential neighborhood in Oslo, Norway, known for its central location and the presence of Lovisenberg Diaconal Hospital and related educational institutions.
-
B.
Seebenstein
Seebenstein is a small Austrian municipality in the state of Lower Austria, known for its historic Seebenstein Castle and scenic location near the eastern edge of the Alps.
-
C.
Willenberg
Willenberg is the former German name of the town now known as Wielbark, located in northern Poland.
-
D.
Hasliberg
Hasliberg is a Swiss alpine village and municipality in the canton of Bern, known for its mountain scenery and ski and hiking resort facilities.
-
E.
Gilserberg
Gilserberg is a small municipality in the German state of Hesse, known for its rural character and location within the Schwalm-Eder district.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157543d688190a151fade71880131 |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:42 p.m.