Triple

T526329
Position Surface form Disambiguated ID Type / Status
Subject France Télévisions E10925 entity
Predicate hasSubsidiary P254 FINISHED
Object France 4 E67390 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 4 | Statement: [France Télévisions, hasSubsidiary, France 4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France 4
Context triple: [France Télévisions, hasSubsidiary, France 4]
  • A. France 4 chosen
    France 4 is a French public television channel, part of the France Télévisions group, known for broadcasting youth-oriented and family entertainment programming.
  • B. France 5
    France 5 is a French public television channel known for its focus on educational, cultural, and documentary programming.
  • C. France
    France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
  • D. 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.
  • E. France Ô
    France Ô was a French public television channel dedicated to programming from France’s overseas departments and territories, operated by the France Télévisions group.
  • 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_69a2e84b16c4819088d284c47c3a7968 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1d0d22081908aad915482d39e74 completed Feb. 28, 2026, 1:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e62e2b3c81908215dab8c0717495 completed March 2, 2026, 1:21 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.