Triple
T10372203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NORD-500 |
E244410
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Norsk Data |
E48799
|
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: Norsk Data | Statement: [NORD-500, manufacturer, Norsk Data]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norsk Data Context triple: [NORD-500, manufacturer, Norsk Data]
-
A.
Norsk Data
chosen
Norsk Data was a Norwegian computer company best known for producing the NORD series of minicomputers during the 1970s and 1980s.
-
B.
Rossum Corporation
Rossum Corporation is a powerful and morally dubious tech conglomerate in the TV series "Dollhouse," responsible for the mind-wiping and imprinting technology used to control human "dolls."
-
C.
International Computers Limited
International Computers Limited was a major British computer manufacturer and information technology company that played a significant role in the UK computing industry during the mid-to-late 20th century.
-
D.
Finn.no AS
Finn.no AS is a leading Norwegian online marketplace company best known for its classified ads platform for jobs, real estate, vehicles, and goods.
-
E.
Unisys
Unisys is an American global information technology company known for providing IT services, software, and infrastructure solutions to government and commercial clients.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e97ed09c8190a3627aa7b5eea62f |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fb8e96e081908282bb0f82719abe |
completed | April 9, 2026, 7:18 p.m. |
Created at: April 6, 2026, 12:01 p.m.