Triple

T6038113
Position Surface form Disambiguated ID Type / Status
Subject Ben Weyts E134472 entity
Predicate name P16 FINISHED
Object Ben Weyts E134472 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: Ben Weyts | Statement: [Ben Weyts, name, Ben Weyts]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ben Weyts
Context triple: [Ben Weyts, name, Ben Weyts]
  • A. Ben Weyts chosen
    Ben Weyts is a Belgian politician from Flanders who has served in prominent roles within the Flemish government, particularly in areas such as education and mobility.
  • B. Bart De Wever
    Bart De Wever is a prominent Belgian politician known as a leading figure of Flemish nationalism and a key power broker in contemporary Belgian politics.
  • C. Kris Peeters
    Kris Peeters is a Belgian politician from the Christian Democratic and Flemish (CD&V) party who served as Minister-President of Flanders and later as a Member of the European Parliament.
  • D. Cédric Van Styvendael
    Cédric Van Styvendael is a French politician who serves as the mayor of the city of Villeurbanne, near Lyon.
  • E. Sébastien Jodogne
    Sébastien Jodogne is a free software developer best known for creating the open-source medical imaging platform Orthanc and for his significant contributions to open healthcare technologies.
  • 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_69c00875db5c819099dd5bb833ec43c2 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056ccac948190a27547878d4db8e4 completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11cfbb4cc81909736d5d041dd0b23 completed March 23, 2026, 10:59 a.m.
Created at: March 22, 2026, 4:08 p.m.