Triple

T13217998
Position Surface form Disambiguated ID Type / Status
Subject Pierre Lazareff E314671 entity
Predicate employer P7 FINISHED
Object France-Soir
France-Soir is a French daily newspaper that became one of the country’s most widely read popular papers in the mid-20th century.
E1028394 NE FINISHED

How this triple was built (4 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-Soir | Statement: [Pierre Lazareff, employer, France-Soir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France-Soir
Context triple: [Pierre Lazareff, employer, France-Soir]
  • A. Le Figaro
    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. Le Matin
    Le Matin is a prominent French daily newspaper that was especially influential in the late 19th and early 20th centuries.
  • C. Le Monde
    Le Monde is a leading French daily newspaper known for its in-depth political, cultural, and international reporting.
  • D. La Presse
    La Presse is a prominent French-language newspaper historically known for serializing major literary works and influencing public opinion in France.
  • 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. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: France-Soir
Triple: [Pierre Lazareff, employer, France-Soir]
Generated description
France-Soir is a French daily newspaper that became one of the country’s most widely read popular papers in the mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: France-Soir
Target entity description: France-Soir is a French daily newspaper that became one of the country’s most widely read popular papers in the mid-20th century.
  • A. Le Figaro
    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. Le Matin
    Le Matin is a prominent French daily newspaper that was especially influential in the late 19th and early 20th centuries.
  • C. Le Monde
    Le Monde is a leading French daily newspaper known for its in-depth political, cultural, and international reporting.
  • D. La Presse
    La Presse is a prominent French-language newspaper historically known for serializing major literary works and influencing public opinion in France.
  • 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. chosen

Provenance (5 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf392e08190949ee4d194566395 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff2085f88190be8cfc309d21f9cb completed May 3, 2026, 7:54 a.m.
NEDg Description generation batch_69f7036009808190aea595cd542e0cf1 completed May 3, 2026, 8:12 a.m.
NED2 Entity disambiguation (via description) batch_69f7040e32a4819083a9f4efe96fd9ca completed May 3, 2026, 8:15 a.m.
Created at: April 9, 2026, 9:18 p.m.