Triple

T11090270
Position Surface form Disambiguated ID Type / Status
Subject ND-500 E262231 entity
Predicate producedBy P490 FINISHED
Object Norsk Data AS 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 AS | Statement: [ND-500, producedBy, Norsk Data AS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norsk Data AS
Context triple: [ND-500, producedBy, Norsk Data AS]
  • 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. 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.
  • C. 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."
  • D. Scala A/S
    Scala A/S is a company known for developing specialized measurement and control instruments, including the Scala MM400.
  • E. Innobase Oy
    Innobase Oy is a Finnish software company best known for creating the InnoDB transactional storage engine used in MySQL databases.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799e96ca08190838c8a04d1eb2a16 completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e42d66ded88190877a20a10f012d6b completed April 19, 2026, 1:18 a.m.
Created at: April 8, 2026, 9:27 p.m.