Triple

T22776183
Position Surface form Disambiguated ID Type / Status
Subject Rennebu E563705 entity
Predicate hasRiver P165 FINISHED
Object Orkla 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: Orkla | Statement: [Rennebu, hasRiver, Orkla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orkla
Context triple: [Rennebu, hasRiver, Orkla]
  • A. Orkla
    Orkla is a leading Norwegian conglomerate primarily focused on branded consumer goods, with significant operations across the Nordic and Baltic regions and parts of Central Europe and India.
  • B. Orkla chosen
    Orkla is a major river in Trøndelag county, Norway, known for its scenic valley and renowned salmon fishing.
  • C. Norse Atlantic ASA
    Norse Atlantic ASA is a Norwegian aviation company that owns and operates the low-cost long-haul carrier Norse Atlantic Airways, focusing primarily on transatlantic routes.
  • D. Borregaard
    Borregaard is a Norwegian biorefinery company that produces advanced and sustainable bio-based chemicals and materials from wood.
  • E. Kvaerner
    Kvaerner is a Norwegian engineering and construction company historically prominent in the shipbuilding and offshore oil and gas 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_69e24554497c819080b996e071de27c2 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17b61acf881909d9f54e0966ee3cc completed April 29, 2026, 3:30 a.m.
Created at: April 17, 2026, 3:28 p.m.