Triple

T3689916
Position Surface form Disambiguated ID Type / Status
Subject Raymond Aron E78317 entity
Predicate employer P7 FINISHED
Object Le Figaro E349219 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: Le Figaro | Statement: [Raymond Aron, employer, Le Figaro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Le Figaro
Context triple: [Raymond Aron, employer, Le Figaro]
  • A. Le Figaro chosen
    Le Figaro is one of France’s oldest and most influential daily newspapers, known for its conservative editorial stance and major role in the country’s cultural and political life.
  • B. La Presse
    La Presse is a prominent French-language newspaper historically known for serializing major literary works and influencing public opinion in France.
  • C. Le Monde
    Le Monde is a leading French daily newspaper known for its in-depth political, cultural, and international reporting.
  • D. Le Dauphiné Libéré
    Le Dauphiné Libéré is a regional French daily newspaper based in southeastern France, known for its coverage of local news and its historical role in organizing major cycling events.
  • E. Revue de Paris
    Revue de Paris was a prominent 19th-century French literary periodical that published major works by leading authors of the time.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4cb47208190b1321af859d02c51 completed March 8, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3c5b6488190afb8cc599d633a96 completed March 14, 2026, 2:11 a.m.
Created at: March 8, 2026, 3:26 p.m.