Triple

T3778009
Position Surface form Disambiguated ID Type / Status
Subject NRK E83353 entity
Predicate operatesChannel P5884 FINISHED
Object NRK3
NRK3 is a Norwegian television channel aimed primarily at younger audiences, offering entertainment, series, and cultural programming.
 E83353 NE FINISHED

How this triple was built (4 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: NRK3 | Statement: [NRK, operatesChannel, NRK3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NRK3
Context triple: [NRK, operatesChannel, NRK3]
  • A. NRK
    NRK is Norway’s public broadcasting corporation, known for producing and airing a wide range of national television and radio programming, including major sports events.
  • B. NR
    NR is the standard abbreviation for National Rail, the collective network of passenger railway services in Great Britain.
  • C. NR
    NR is the commonly used abbreviation for the Nordic Council, a regional inter-parliamentary body for cooperation among the Nordic countries.
  • D. NR
    NR is the two-letter ISO 3166-1 alpha-2 country code assigned to the Republic of Nauru.
  • E. RKR
    RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: NRK3
Triple: [NRK, operatesChannel, NRK3]
Generated description
NRK3 is a Norwegian television channel aimed primarily at younger audiences, offering entertainment, series, and cultural programming.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NRK3
Target entity description: NRK3 is a Norwegian television channel aimed primarily at younger audiences, offering entertainment, series, and cultural programming.
  • A. NRK chosen
    NRK is Norway’s public broadcasting corporation, known for producing and airing a wide range of national television and radio programming, including major sports events.
  • B. NR
    NR is the standard abbreviation for National Rail, the collective network of passenger railway services in Great Britain.
  • C. NR
    NR is the commonly used abbreviation for the Nordic Council, a regional inter-parliamentary body for cooperation among the Nordic countries.
  • D. NR
    NR is the two-letter ISO 3166-1 alpha-2 country code assigned to the Republic of Nauru.
  • E. RKR
    RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
  • F. None of above.

Provenance (5 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc5d3dbc8190b6ab118a56acd5a3 completed March 8, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503ea77708190ae55cd1892735b22 completed March 14, 2026, 6:44 a.m.
NEDg Description generation batch_69b50585106c8190aaa1c47b397543ea completed March 14, 2026, 6:51 a.m.
NED2 Entity disambiguation (via description) batch_69b50707d6a4819097f2bca0ebe663b1 completed March 14, 2026, 6:58 a.m.
Created at: March 8, 2026, 3:36 p.m.