Triple

T1622731
Position Surface form Disambiguated ID Type / Status
Subject Lommel SK E35068 entity
Predicate shortName P43 FINISHED
Object Lommel SK E35068 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: Lommel SK | Statement: [Lommel SK, shortName, Lommel SK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lommel SK
Context triple: [Lommel SK, shortName, Lommel SK]
  • A. Lommel SK chosen
    Lommel SK is a Belgian professional football club that competes in the country’s league system and serves as part of City Football Group’s global network of teams.
  • B. 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.
  • C. Vålerenga
    Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
  • D. Lørenskog IF
    Lørenskog IF is a Norwegian sports club best known for its football team, based in Lørenskog near Oslo.
  • E. Lillehammer FK
    Lillehammer FK is a Norwegian football club based in the town of Lillehammer, competing in the lower tiers of the national league 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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909cf3c7481909ddbe6a6596bb0c8 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58ccc80c819088ecd91f0a99a247 completed March 8, 2026, 11:09 a.m.
Created at: March 4, 2026, 7:28 p.m.