Triple

T1057559
Position Surface form Disambiguated ID Type / Status
Subject Office of the Prime Minister of Norway E22830 entity
Predicate shortName P43 FINISHED
Object SMK
SMK is the commonly used abbreviation for the Office of the Prime Minister of Norway, the central executive body that supports the Norwegian Prime Minister and coordinates government policy.
 E121378 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: SMK | Statement: [Office of the Prime Minister of Norway, shortName, SMK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SMK
Context triple: [Office of the Prime Minister of Norway, shortName, SMK]
  • A. .sm
    .sm is the country code top-level domain (ccTLD) assigned to the Republic of San Marino for use on the internet.
  • B. Sk
    Sk is the currency symbol that was used to denote the Slovak koruna, the former national currency of Slovakia before adoption of the euro.
  • C. Skol
    Skol is a global beer brand, originally developed in Europe, known for its light lager and widespread popularity in markets such as Brazil and parts of Europe.
  • D. SEK
    SEK is the official currency code for the Swedish krona, the national currency of Sweden.
  • E. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • 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: SMK
Triple: [Office of the Prime Minister of Norway, shortName, SMK]
Generated description
SMK is the commonly used abbreviation for the Office of the Prime Minister of Norway, the central executive body that supports the Norwegian Prime Minister and coordinates government policy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SMK
Target entity description: SMK is the commonly used abbreviation for the Office of the Prime Minister of Norway, the central executive body that supports the Norwegian Prime Minister and coordinates government policy.
  • A. .sm
    .sm is the country code top-level domain (ccTLD) assigned to the Republic of San Marino for use on the internet.
  • B. Sk
    Sk is the currency symbol that was used to denote the Slovak koruna, the former national currency of Slovakia before adoption of the euro.
  • C. Skol
    Skol is a global beer brand, originally developed in Europe, known for its light lager and widespread popularity in markets such as Brazil and parts of Europe.
  • D. SEK
    SEK is the official currency code for the Swedish krona, the national currency of Sweden.
  • E. SK
    SK is the postcode area covering Stockport and surrounding parts of Greater Manchester and nearby counties in North West England.
  • F. None of above. chosen

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_69a493dada0481909c43649f9843ea91 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8da80dc8190b79beaf509910725 completed March 1, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bd110ac8190b66163de42bd3034 completed March 7, 2026, 2:53 p.m.
NEDg Description generation batch_69ac3d4b32348190883244f2b8af32a0 completed March 7, 2026, 2:59 p.m.
NED2 Entity disambiguation (via description) batch_69ac3dbf5c70819084a942fc97a9b50f completed March 7, 2026, 3:01 p.m.
Created at: March 1, 2026, 7:42 p.m.