Triple

T2867626
Position Surface form Disambiguated ID Type / Status
Subject Albert Schweitzer E63477 entity
Predicate citizenship P2 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: [Albert Schweitzer, citizenship, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France
Context triple: [Albert Schweitzer, citizenship, 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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfbcebcc81909a78a1787d823e3e completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01d56399881909f5e54f751fe5ad0 completed March 10, 2026, 1:32 p.m.
Created at: March 6, 2026, 10:02 p.m.