Triple
T22962381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SINTEF |
E570934
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | SINTEF Digital |
—
|
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: SINTEF Digital | Statement: [SINTEF, hasSubsidiary, SINTEF Digital]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SINTEF Digital Context triple: [SINTEF, hasSubsidiary, SINTEF Digital]
-
A.
SINTEF
chosen
SINTEF is one of Europe’s largest independent research organizations, based in Norway and known for applied research and innovation across technology and the natural sciences.
-
B.
Norwegian Computing Center
The Norwegian Computing Center is a leading Norwegian research institute specializing in applied information technology, statistics, and machine learning.
-
C.
Norwegian Museum of Science and Technology
The Norwegian Museum of Science and Technology is a national museum in Oslo dedicated to the history, exploration, and popularization of science, technology, industry, and medicine.
-
D.
Norsk Data
Norsk Data was a Norwegian computer company best known for producing the NORD series of minicomputers during the 1970s and 1980s.
-
E.
Intility AS
Intility AS is a Norwegian IT company that provides cloud-based platform and infrastructure services to businesses.
- 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f594fc8190816418486b798198 |
completed | April 29, 2026, 3:58 a.m. |
Created at: April 17, 2026, 3:47 p.m.