Triple

T18851162
Position Surface form Disambiguated ID Type / Status
Subject Swedish Trade Union Confederation E461043 entity
Predicate shortName P43 FINISHED
Object LO
LO is Sweden’s largest national trade union confederation, representing a broad coalition of blue-collar workers across multiple industries.
 E1346062 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: LO | Statement: [Swedish Trade Union Confederation, shortName, LO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LO
Context triple: [Swedish Trade Union Confederation, shortName, LO]
  • A. LO
    LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
  • B. LO
    LO was the New York Stock Exchange ticker symbol for Lorillard Tobacco Company, a major American tobacco manufacturer best known for brands like Newport.
  • C. LO
    LO is the regional vehicle registration code assigned to the city of Vanadzor in Armenia.
  • D. LO
    LO is the vehicle registration code used on license plates for vehicles registered in the Province of Lodi in Italy.
  • E. LO
    LO is the IATA airline designator used for LOT Polish Airlines, the flag carrier 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: LO
Triple: [Swedish Trade Union Confederation, shortName, LO]
Generated description
LO is Sweden’s largest national trade union confederation, representing a broad coalition of blue-collar workers across multiple industries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LO
Target entity description: LO is Sweden’s largest national trade union confederation, representing a broad coalition of blue-collar workers across multiple industries.
  • A. LO
    LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
  • B. LO
    LO is the IATA airline designator used for LOT Polish Airlines, the flag carrier of Poland.
  • C. LO
    LO was the New York Stock Exchange ticker symbol for Lorillard Tobacco Company, a major American tobacco manufacturer best known for brands like Newport.
  • D. LO
    LO is the vehicle registration code used on license plates for the city of Loznica in Serbia.
  • E. LO
    LO is the vehicle registration code used on license plates for vehicles registered in the Province of Lodi in Italy.
  • 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_69d8dcfa11e4819090ab1ef5bdcd2b2e completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c05995e88190b189864fcbda68e5 completed April 20, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0567778ef08190af337b59cb345eed completed May 14, 2026, 6:11 a.m.
NEDg Description generation batch_6a056c57c32481908b14f6a830a0e3e9 completed May 14, 2026, 6:31 a.m.
NED2 Entity disambiguation (via description) batch_6a056cf897188190b46a7c662c639d88 completed May 14, 2026, 6:34 a.m.
Created at: April 10, 2026, 11:56 a.m.