Triple

T35068992
Position Surface form Disambiguated ID Type / Status
Subject Cercle Saint-Pierre Limoges E1011813 entity
Predicate EuropeanTitles P182073 FINISHED
Object multiple European club titles LITERAL 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: multiple European club titles | Statement: [Cercle Saint-Pierre Limoges, EuropeanTitles, multiple European club titles]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: EuropeanTitles
Context triple: [Cercle Saint-Pierre Limoges, EuropeanTitles, multiple European club titles]
  • A. worldTitles
    Indicates that an entity has won one or more world championship titles in a given field or competition.
  • B. mastersTitles
    Indicates that one entity holds one or more master's degree titles associated with another entity (such as an institution, field, or program).
  • C. EuropeanTitleCount
    Indicates the number of European titles (such as championships or major continental honors) that an entity has won or holds.
  • D. EuropeanChampionshipTitles
    Indicates the number of European Championship titles an entity has won.
  • E. worldChampionshipTitles
    Indicates the number of world championship titles an entity has won.
  • F. None of above. chosen

Provenance (4 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_69f76dd193108190af2528186f25b72a completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7865578d48190bf90e470634fd97d completed May 3, 2026, 5:31 p.m.
PD Predicate disambiguation batch_69f7841812f081909d878955d114088e completed May 3, 2026, 5:21 p.m.
PDg Predicate description generation batch_69f78575917481909a3defd6a4c366bd completed May 3, 2026, 5:27 p.m.
Created at: May 3, 2026, 4:01 p.m.