Triple

T5707050
Position Surface form Disambiguated ID Type / Status
Subject Lillestrøm SK E125809 entity
Predicate nickname P55 FINISHED
Object LSK
LSK is a common abbreviation for Lillestrøm SK, a Norwegian football club known for competing in the country’s top divisions and having a strong local fan base.
 E539248 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: LSK | Statement: [Lillestrøm SK, nickname, LSK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LSK
Context triple: [Lillestrøm SK, nickname, LSK]
  • A. BSK
    BSK is the National Rail station code for Basingstoke railway station in Hampshire, England.
  • B. LSG
    LSG is the standard French abbreviation for the Louis Segond Bible, a widely used Protestant translation of the Scriptures into French.
  • C. LGSK
    LGSK is the ICAO airport code for Skiathos Island National Airport in Greece, known for its short runway and dramatic low-altitude aircraft approaches.
  • D. RSL
    RSL is the shading language used in Pixar's RenderMan system to define the appearance of surfaces, lights, and volumes in high-end computer graphics rendering.
  • E. RSL
    RSL is the commonly used abbreviation for the Royal Society of Literature, a prestigious UK organization dedicated to the advancement of literature.
  • 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: LSK
Triple: [Lillestrøm SK, nickname, LSK]
Generated description
LSK is a common abbreviation for Lillestrøm SK, a Norwegian football club known for competing in the country’s top divisions and having a strong local fan base.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LSK
Target entity description: LSK is a common abbreviation for Lillestrøm SK, a Norwegian football club known for competing in the country’s top divisions and having a strong local fan base.
  • A. BSK
    BSK is the National Rail station code for Basingstoke railway station in Hampshire, England.
  • B. LSG
    LSG is the standard French abbreviation for the Louis Segond Bible, a widely used Protestant translation of the Scriptures into French.
  • C. LGSK
    LGSK is the ICAO airport code for Skiathos Island National Airport in Greece, known for its short runway and dramatic low-altitude aircraft approaches.
  • D. RSL
    RSL is the shading language used in Pixar's RenderMan system to define the appearance of surfaces, lights, and volumes in high-end computer graphics rendering.
  • E. RSL
    RSL is the commonly used abbreviation for the Royal Society of Literature, a prestigious UK organization dedicated to the advancement of literature.
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024892fd88190a91133fc88365410 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a6c17608190a9a808c2c77d937c completed March 22, 2026, 9:09 p.m.
NEDg Description generation batch_69c05b7b57d481909f830a6cf7f59c3e completed March 22, 2026, 9:13 p.m.
NED2 Entity disambiguation (via description) batch_69c05c2046c48190a5d100f2dfad8d7b completed March 22, 2026, 9:16 p.m.
Created at: March 22, 2026, 3:45 p.m.