Triple

T5046515
Position Surface form Disambiguated ID Type / Status
Subject Thun E113677 entity
Predicate hasSportsTeam P330 FINISHED
Object FC Thun E443697 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: FC Thun | Statement: [Thun, hasSportsTeam, FC Thun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FC Thun
Context triple: [Thun, hasSportsTeam, FC Thun]
  • A. FC Thun chosen
    FC Thun is a Swiss professional football club based in Thun that competes in the country’s league system and is known for its regional presence and occasional appearances in European competitions.
  • B. Stade de Suisse
    Stade de Suisse is a modern football stadium in Bern, Switzerland, best known as the home ground of Swiss club BSC Young Boys.
  • C. Yverdon-Sport FC
    Yverdon-Sport FC is a Swiss professional football club based in Yverdon-les-Bains that competes in the country’s league system.
  • D. FC Zürich
    FC Zürich is a Swiss professional football club based in Zurich, known for its multiple national championships and participation in European competitions.
  • E. FC Basel
    FC Basel is a prominent Swiss football club based in Basel, known for its domestic success and regular participation in European competitions.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73fe99688190961708f5d8eb6bff completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c8e1fc481908faf1042ee7f49e9 completed March 21, 2026, 1:26 p.m.
Created at: March 20, 2026, 1:37 p.m.