Triple
T21889172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FFI |
E540490
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object | Kjeller |
—
|
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: Kjeller | Statement: [FFI, headquartersLocation, Kjeller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kjeller Context triple: [FFI, headquartersLocation, Kjeller]
-
A.
Kjeller
chosen
Kjeller is a research-focused village in Lillestrøm, Norway, known as a major hub for defense, aviation, and technology institutions.
-
B.
Steinkjer
Steinkjer is a town and municipality in central Norway that serves as an important regional center and administrative hub in Trøndelag county.
-
C.
Bjerkreim
Bjerkreim is a rural municipality in southwestern Norway known for its rivers, salmon fishing, and agricultural landscape.
-
D.
Koppang
Koppang is a small village in Innlandet county, Norway, known as a local service and transport hub in the Østerdalen valley.
-
E.
Kongsberg
Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
- 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_69e0c47a95908190ae3e19b716accb3d |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f118ef2b648190bbd78f6b3958d2ee |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 16, 2026, 7:06 p.m.