Triple
T12190586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tietoevry |
E290449
|
entity |
| Predicate | hasSubsidiary |
P254
|
FINISHED |
| Object | Tietoevry Care |
E290449
|
NE FINISHED |
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: Tietoevry Care | Statement: [Tietoevry, hasSubsidiary, Tietoevry Care]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tietoevry Care Context triple: [Tietoevry, hasSubsidiary, Tietoevry Care]
-
A.
Tietoevry
chosen
Tietoevry is a Nordic-based IT services and software company specializing in digital transformation, cloud, and data-driven solutions for businesses and public sector organizations.
-
B.
Infotech Oulu
Infotech Oulu is a multidisciplinary research institute at the University of Oulu focused on information technology and related fields.
-
C.
Intility AS
Intility AS is a Norwegian IT company that provides cloud-based platform and infrastructure services to businesses.
-
D.
Vives Network
Vives Network is a collaborative association of universities and higher education institutions in the Catalan-speaking regions that promotes academic, cultural, and research cooperation.
-
E.
Synamedia
Synamedia is a video software and security company that provides solutions for pay-TV operators and streaming providers to deliver, protect, and monetize their content.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c5340248190b79379423f3a3ca1 |
completed | April 10, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6b240f88190af916054869c3b95 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.