Triple

T12746702
Position Surface form Disambiguated ID Type / Status
Subject Gabriel Landeskog E304622 entity
Predicate familyName P18 FINISHED
Object Landeskog
Landeskog is the surname of Swedish professional ice hockey player Gabriel Landeskog, a prominent NHL forward and longtime captain of the Colorado Avalanche.
 E1002399 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: Landeskog | Statement: [Gabriel Landeskog, familyName, Landeskog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Landeskog
Context triple: [Gabriel Landeskog, familyName, Landeskog]
  • A. Hesselberg
    Hesselberg is a prominent hill in Bavaria, Germany, known as the highest elevation of the Franconian Alb region.
  • B. Skarnes
    Skarnes is a village in Norway that serves as an administrative and commercial center in the Glåmdalen region.
  • C. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • D. Hjorthagen
    Hjorthagen is a residential district in northeastern Stockholm, Sweden, known for its mix of historic workers’ housing and modern developments near the Royal National City Park and the Värtan harbor area.
  • E. Thamerdal
    Thamerdal is a residential neighborhood within the Dutch town of Uithoorn in the province of North Holland.
  • 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: Landeskog
Triple: [Gabriel Landeskog, familyName, Landeskog]
Generated description
Landeskog is the surname of Swedish professional ice hockey player Gabriel Landeskog, a prominent NHL forward and longtime captain of the Colorado Avalanche.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Landeskog
Target entity description: Landeskog is the surname of Swedish professional ice hockey player Gabriel Landeskog, a prominent NHL forward and longtime captain of the Colorado Avalanche.
  • A. Hesselberg
    Hesselberg is a prominent hill in Bavaria, Germany, known as the highest elevation of the Franconian Alb region.
  • B. Skarnes
    Skarnes is a village in Norway that serves as an administrative and commercial center in the Glåmdalen region.
  • C. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • D. Hjorthagen
    Hjorthagen is a residential district in northeastern Stockholm, Sweden, known for its mix of historic workers’ housing and modern developments near the Royal National City Park and the Värtan harbor area.
  • E. Thamerdal
    Thamerdal is a residential neighborhood within the Dutch town of Uithoorn in the province of North Holland.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96bd58d30819082af4edb4cd0b4ab completed April 10, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684ee2ab4819099194d115d2e5a15 completed May 2, 2026, 11:12 p.m.
NEDg Description generation batch_69f6887fe8a08190b61831a13b656a89 completed May 2, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_69f6890ad3188190be5a5b80e81ab958 completed May 2, 2026, 11:30 p.m.
Created at: April 9, 2026, 5:27 p.m.