Triple

T14427843
Position Surface form Disambiguated ID Type / Status
Subject Kun E357740 entity
Predicate alsoKnownAs P39 FINISHED
Object Comani E357741 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: Comani | Statement: [Kun, alsoKnownAs, Comani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Comani
Context triple: [Kun, alsoKnownAs, Comani]
  • A. Comani chosen
    Comani is an alternative name for the Cumans, a medieval nomadic Turkic people who inhabited the Eurasian steppe and played a significant role in Eastern European history.
  • B. Franck Kessié
    Franck Kessié is an Ivorian professional footballer known as a powerful, box-to-box midfielder who has starred for clubs like AC Milan and FC Barcelona as well as the Ivory Coast national team.
  • C. Kalidou Koulibaly
    Kalidou Koulibaly is a Senegalese professional footballer renowned as one of the top central defenders of his generation, known for his strength, leadership, and performances in European and international football.
  • D. Wilfried Mbappé
    Wilfried Mbappé is a French football coach and former player best known as the father and early mentor of superstar forward Kylian Mbappé.
  • E. Hubert Koundé
    Hubert Koundé is a French actor and filmmaker known for his roles in acclaimed films such as "La Haine" and various international productions.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91154de881909266ae88d1545685 completed April 14, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bcfa1d88190b59cefd3e305f55f completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:18 a.m.