Triple

T2727336
Position Surface form Disambiguated ID Type / Status
Subject Ferdinand E60224 entity
Predicate hasVariant P455 FINISHED
Object Ferrand
Ferrand is a given name and surname of French origin, related to the name Ferdinand.
 E292535 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: Ferrand | Statement: [Ferdinand, hasVariant, Ferrand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ferrand
Context triple: [Ferdinand, hasVariant, Ferrand]
  • A. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • B. Fuissé
    Fuissé is a renowned wine-producing village in France’s Burgundy region, particularly famous for its Pouilly-Fuissé Chardonnay wines.
  • C. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • D. Oberkampf
    Oberkampf is a Paris Métro station in the 11th arrondissement, serving as an interchange between lines 5 and 9 near the lively Oberkampf district.
  • E. Meunier
    Meunier is a black grape variety primarily used in Champagne production, valued for adding fruitiness and early maturity to sparkling wine blends.
  • 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: Ferrand
Triple: [Ferdinand, hasVariant, Ferrand]
Generated description
Ferrand is a given name and surname of French origin, related to the name Ferdinand.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ferrand
Target entity description: Ferrand is a given name and surname of French origin, related to the name Ferdinand.
  • A. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • B. Fuissé
    Fuissé is a renowned wine-producing village in France’s Burgundy region, particularly famous for its Pouilly-Fuissé Chardonnay wines.
  • C. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • D. Oberkampf
    Oberkampf is a Paris Métro station in the 11th arrondissement, serving as an interchange between lines 5 and 9 near the lively Oberkampf district.
  • E. Meunier
    Meunier is a black grape variety primarily used in Champagne production, valued for adding fruitiness and early maturity to sparkling wine blends.
  • 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_69ab4b75cd908190b691ef0d1801acda completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdacffa6481909df37335e8fdd595 completed March 7, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6982974819089d0ef4a59cc4085 completed March 10, 2026, 6:13 a.m.
NEDg Description generation batch_69afb7166d788190ac219fe3c3e164fe completed March 10, 2026, 6:15 a.m.
NED2 Entity disambiguation (via description) batch_69afb7acf3588190813bde4428dfe5f4 completed March 10, 2026, 6:18 a.m.
Created at: March 6, 2026, 9:56 p.m.