Triple

T10351776
Position Surface form Disambiguated ID Type / Status
Subject Léon Zitrone E243897 entity
Predicate employer P7 FINISHED
Object France 2 E331152 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: France 2 | Statement: [Léon Zitrone, employer, France 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France 2
Context triple: [Léon Zitrone, employer, France 2]
  • A. France 2 chosen
    France 2 is a major French public television channel that forms part of the France Télévisions group and broadcasts a wide range of news, entertainment, and cultural programming nationwide.
  • B. France 3
    France 3 is a French public television channel known for its regional programming and news coverage as part of the France Télévisions group.
  • C. france.tv
    france.tv is the official online streaming and catch-up TV platform of the French public broadcaster France Télévisions, offering live channels and on-demand programs.
  • D. France Télévisions
    France Télévisions is France’s national public television broadcaster, operating multiple channels and providing a wide range of news, sports, and cultural programming.
  • E. France Info
    France Info is a French public rolling news television channel providing continuous national and international news coverage.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9489f9481908fc1c818e81c1cc2 completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d75095625c819082d4d0976a193e6c completed April 9, 2026, 7:09 a.m.
Created at: April 6, 2026, 11:57 a.m.