Triple

T15216722
Position Surface form Disambiguated ID Type / Status
Subject SK Brann E363654 entity
Predicate hasAbbreviation P43 FINISHED
Object SK Brann E363654 NE FINISHED

How this triple was built (2 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: SK Brann | Statement: [SK Brann, hasAbbreviation, SK Brann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SK Brann
Context triple: [SK Brann, hasAbbreviation, SK Brann]
  • A. SK Brann chosen
    SK Brann is a Norwegian professional football club based in Bergen that competes in the country’s top divisions and has a large, passionate fan base.
  • B. Rosenborg BK
    Rosenborg BK is a Norwegian professional football club from Trondheim, historically one of the country’s most successful teams and a dominant force in the Eliteserien.
  • C. Stabæk Fotball
    Stabæk Fotball is a Norwegian professional football club based in Bærum, known for competing in the country’s top divisions and developing notable players and coaches.
  • D. Lillestrøm SK
    Lillestrøm SK is a Norwegian professional football club known for its passionate fan base, historic success in domestic competitions, and intense rivalry with other Oslo-area teams.
  • E. Bryne FK
    Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff01dc23d081908ad6985bae5741ce completed May 9, 2026, 9:43 a.m.
Created at: April 10, 2026, 3:11 a.m.