Triple

T8804585
Position Surface form Disambiguated ID Type / Status
Subject Harvey E209494 entity
Predicate hasVariantForm P457 FINISHED
Object Hervé
Hervé is a French given name, often considered a variant of the English name Harvey, and is commonly used for males in French-speaking regions.
 E776812 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: Hervé | Statement: [Harvey, hasVariantForm, Hervé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hervé
Context triple: [Harvey, hasVariantForm, Hervé]
  • A. Gérard
    Gérard is a French given name, equivalent to the Germanic name Gerhard, commonly used in French-speaking countries.
  • B. Benoît
    Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
  • C. Étienne
    Étienne is the given first name of the French Symbolist poet Stéphane Mallarmé.
  • D. Stéphane
    Stéphane is a French masculine given name, equivalent to Stephen in English, commonly used in Francophone countries.
  • E. Jérôme
    Jérôme is a masculine given name of French origin, famously borne by Jérôme Bonaparte, the youngest brother of Napoleon I.
  • 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: Hervé
Triple: [Harvey, hasVariantForm, Hervé]
Generated description
Hervé is a French given name, often considered a variant of the English name Harvey, and is commonly used for males in French-speaking regions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hervé
Target entity description: Hervé is a French given name, often considered a variant of the English name Harvey, and is commonly used for males in French-speaking regions.
  • A. Gérard
    Gérard is a French given name, equivalent to the Germanic name Gerhard, commonly used in French-speaking countries.
  • B. Benoît
    Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
  • C. Étienne
    Étienne is the given first name of the French Symbolist poet Stéphane Mallarmé.
  • D. Stéphane
    Stéphane is a French masculine given name, equivalent to Stephen in English, commonly used in Francophone countries.
  • E. Jérôme
    Jérôme is a masculine given name of French origin, famously borne by Jérôme Bonaparte, the youngest brother of Napoleon I.
  • 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_69ca836320e48190b5cf585b90a322c4 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fbe15b081909e87dab6b5029d04 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cffd6b7eb88190b878165e41cf1df8 completed April 3, 2026, 5:48 p.m.
NEDg Description generation batch_69d003903e188190aed2683d969602b9 completed April 3, 2026, 6:14 p.m.
NED2 Entity disambiguation (via description) batch_69d003fba47c819087a2be245fc9da6a completed April 3, 2026, 6:16 p.m.
Created at: March 30, 2026, 6:44 p.m.