Triple

T19220327
Position Surface form Disambiguated ID Type / Status
Subject Flisa E480594 entity
Predicate hasSportsClub P346 FINISHED
Object Flisa IL NE NERFINISHED

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: Flisa IL | Statement: [Flisa, hasSportsClub, Flisa IL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flisa IL
Context triple: [Flisa, hasSportsClub, Flisa IL]
  • A. Flisa chosen
    Flisa is a small town in Innlandet county, Norway, known as a local commercial and administrative center in the Glåmdalen region.
  • B. Filisur
    Filisur is a picturesque Swiss village in the canton of Graubünden, known for its historic center and proximity to the famous Landwasser Viaduct on the Rhaetian Railway.
  • C. Ilisan
    Ilisan is a prominent town in the Remo region of Ogun State, southwestern Nigeria, known for its role as a local commercial and educational center.
  • D. Iliʻili
    Iliʻili is a village in American Samoa that serves as an important local center within Tualauta County on the island of Tutuila.
  • E. Ilz
    The Ilz is a river in southeastern Germany that flows through the Bavarian Forest before joining the Danube near Passau.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8cb8c348190b52075823911c869 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa3e8d488190a93fb743dabd0ffb completed April 20, 2026, 10:04 a.m.
Created at: April 10, 2026, 1:24 p.m.