Triple

T3964750
Position Surface form Disambiguated ID Type / Status
Subject Nuuk E92187 entity
Predicate hasStadium P105 FINISHED
Object Nuuk Stadium
Nuuk Stadium is the main multi-purpose sports venue in Greenland’s capital, primarily used for football and other community events.
 E402709 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: Nuuk Stadium | Statement: [Nuuk, hasStadium, Nuuk Stadium]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nuuk Stadium
Context triple: [Nuuk, hasStadium, Nuuk Stadium]
  • A. Ullevaal Stadion
    Ullevaal Stadion is Norway’s national football stadium and a major sports and events arena located in Oslo.
  • B. Alfheim Stadion
    Alfheim Stadion is a football stadium in Tromsø, Norway, best known as the home ground of the Norwegian club Tromsø IL.
  • C. Viking Stadion
    Viking Stadion is a football stadium in Stavanger, Norway, primarily serving as the home ground of Viking FK.
  • D. Åråsen Stadion
    Åråsen Stadion is a football stadium in Lillestrøm, Norway, best known as the main home ground of Lillestrøm SK and a prominent venue in Norwegian football.
  • E. Aspmyra Stadion
    Aspmyra Stadion is a football stadium in Bodø, Norway, best known as the home ground of FK Bodø/Glimt.
  • 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: Nuuk Stadium
Triple: [Nuuk, hasStadium, Nuuk Stadium]
Generated description
Nuuk Stadium is the main multi-purpose sports venue in Greenland’s capital, primarily used for football and other community events.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nuuk Stadium
Target entity description: Nuuk Stadium is the main multi-purpose sports venue in Greenland’s capital, primarily used for football and other community events.
  • A. Ullevaal Stadion
    Ullevaal Stadion is Norway’s national football stadium and a major sports and events arena located in Oslo.
  • B. Alfheim Stadion
    Alfheim Stadion is a football stadium in Tromsø, Norway, best known as the home ground of the Norwegian club Tromsø IL.
  • C. Viking Stadion
    Viking Stadion is a football stadium in Stavanger, Norway, primarily serving as the home ground of Viking FK.
  • D. Åråsen Stadion
    Åråsen Stadion is a football stadium in Lillestrøm, Norway, best known as the main home ground of Lillestrøm SK and a prominent venue in Norwegian football.
  • E. Aspmyra Stadion
    Aspmyra Stadion is a football stadium in Bodø, Norway, best known as the home ground of FK Bodø/Glimt.
  • 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_69aed96624188190ac8c45bb57ab72b5 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef97326888190bbfe15b218e3112e completed March 9, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b533be4a688190a7d011ae2858e6ed completed March 14, 2026, 10:09 a.m.
NEDg Description generation batch_69b537cc86e88190bae10e740d8c3ec7 completed March 14, 2026, 10:26 a.m.
NED2 Entity disambiguation (via description) batch_69b538595d2481908812ab03cdb94659 completed March 14, 2026, 10:28 a.m.
Created at: March 9, 2026, 3:31 p.m.