Triple

T5248905
Position Surface form Disambiguated ID Type / Status
Subject Scaniarinken E118531 entity
Predicate hasTenant P3277 FINISHED
Object Södertälje SK E506228 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: Södertälje SK | Statement: [Scaniarinken, hasTenant, Södertälje SK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Södertälje SK
Context triple: [Scaniarinken, hasTenant, Södertälje SK]
  • A. Södertälje SK chosen
    Södertälje SK is a Swedish professional ice hockey club based in Södertälje, known for its long history and multiple national championships.
  • B. Södertälje FK
    Södertälje FK is a Swedish football club based in Södertälje, known locally for its competitive presence and rivalry with neighboring club Syrianska FC.
  • C. Östersunds FK
    Östersunds FK is a Swedish professional football club known for its rapid rise through the leagues and notable performances in domestic and European competitions.
  • D. Lidingö SK
    Lidingö SK is a Swedish multi-sport club based in Lidingö, known especially for its athletics and orienteering activities.
  • E. Djurgårdens IF
    Djurgårdens IF is a prominent Swedish sports club from Stockholm, best known for its successful ice hockey and football teams and large, passionate fan base.
  • 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_69bd4468aacc8190a8196f71855cdf4f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b787b34819081af96de9355bb4f completed March 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06bc1c0c8190abc1e24f99621e49 completed March 21, 2026, 8:59 p.m.
Created at: March 20, 2026, 1:50 p.m.