Triple

T4857675
Position Surface form Disambiguated ID Type / Status
Subject Handschar Division E108575 entity
Predicate trainingLocation P40 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: [Handschar Division, trainingLocation, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France
Context triple: [Handschar Division, trainingLocation, 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. Lafrançaise, France
    Lafrançaise is a small commune in the Tarn-et-Garonne department of southern France, known for its rural charm and traditional French village atmosphere.
  • C. 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.
  • D. France and Germany
    France and Germany are two major neighboring European countries that share deep historical ties, a central role in the European Union, and a long land border.
  • E. France 5
    France 5 is a French public television channel known for its focus on educational, cultural, and documentary programming.
  • 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_69bd440a89548190a5f14ba6da6b97dc completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d3f24688190b2f2b79bcde96973 completed March 20, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5cb34004819086809b4a7071f4a5 completed March 21, 2026, 8:54 a.m.
Created at: March 20, 2026, 1:26 p.m.