Triple

T3033621
Position Surface form Disambiguated ID Type / Status
Subject Magique E82954 entity
Predicate countryOfEvent P1083 FINISHED
Object France E861 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 | Statement: [Magique, countryOfEvent, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France
Context triple: [Magique, countryOfEvent, France]
  • A. France chosen
    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.
  • B. 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.
  • C. France 5
    France 5 is a French public television channel known for its focus on educational, cultural, and documentary programming.
  • D. France 4
    France 4 is a French public television channel, part of the France Télévisions group, known for broadcasting youth-oriented and family entertainment programming.
  • E. France and Italy
    France and Italy are neighboring European countries that share a long Alpine border, rich cultural heritage, and significant historical, economic, and touristic ties.
  • 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_69ad8b21a62881908ec5dd4fba4a187c completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9af13ce48190bda4f5ca0ffe6285 completed March 8, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1dea6b460819087d7186efc901ef2 completed March 11, 2026, 9:29 p.m.
Created at: March 8, 2026, 3:01 p.m.