Triple

T12661743
Position Surface form Disambiguated ID Type / Status
Subject Pierre Fournier E302441 entity
Predicate familyName P18 FINISHED
Object Fournier
Fournier is a French surname borne by numerous notable figures across fields such as music, sports, politics, and the arts.
 E996401 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: Fournier | Statement: [Pierre Fournier, familyName, Fournier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fournier
Context triple: [Pierre Fournier, familyName, Fournier]
  • A. Facio
    Facio is a surname of Spanish and Italian origin borne by various notable individuals, including figures in politics, the arts, and academia.
  • B. Codman
    Codman is a surname most notably associated with Ogden Codman Jr., an influential American architect and interior decorator of the late 19th and early 20th centuries.
  • C. Trioditis
    Trioditis is an epithet of the Greek goddess Hecate that emphasizes her association with crossroads and liminal spaces.
  • D. Trousseau
    Trousseau is a red wine grape variety from France’s Jura region, known for producing deeply colored, aromatic wines with good structure and aging potential.
  • E. Graefekiez
    Graefekiez is a popular, village-like neighborhood in Berlin’s Kreuzberg district known for its leafy streets, cafés, and vibrant local culture.
  • 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: Fournier
Triple: [Pierre Fournier, familyName, Fournier]
Generated description
Fournier is a French surname borne by numerous notable figures across fields such as music, sports, politics, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fournier
Target entity description: Fournier is a French surname borne by numerous notable figures across fields such as music, sports, politics, and the arts.
  • A. Facio
    Facio is a surname of Spanish and Italian origin borne by various notable individuals, including figures in politics, the arts, and academia.
  • B. Codman
    Codman is a surname most notably associated with Ogden Codman Jr., an influential American architect and interior decorator of the late 19th and early 20th centuries.
  • C. Trioditis
    Trioditis is an epithet of the Greek goddess Hecate that emphasizes her association with crossroads and liminal spaces.
  • D. Trousseau
    Trousseau is a red wine grape variety from France’s Jura region, known for producing deeply colored, aromatic wines with good structure and aging potential.
  • E. Graefekiez
    Graefekiez is a popular, village-like neighborhood in Berlin’s Kreuzberg district known for its leafy streets, cafés, and vibrant local culture.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9617c5b888190b37d4ede139bb49e completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6688819fc8190bc03a1a11f96d25f completed May 2, 2026, 9:11 p.m.
NEDg Description generation batch_69f669c9454081909d39d5bb7082fb00 completed May 2, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_69f66b619c88819098acbfb60fac9921 completed May 2, 2026, 9:23 p.m.
Created at: April 9, 2026, 5:19 p.m.