Triple

T10250722
Position Surface form Disambiguated ID Type / Status
Subject Calixto E240331 entity
Predicate etymologicalRelation P2530 FINISHED
Object Calixte
Calixte is a given name of Latin origin, commonly used in French-speaking regions and derived from the same root as Calixto.
E854848 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: Calixte | Statement: [Calixto, etymologicalRelation, Calixte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Calixte
Context triple: [Calixto, etymologicalRelation, Calixte]
  • A. Clément
    Clément is a French given name, equivalent to Clement in English, commonly used for males.
  • B. Maxime Siroux
    Maxime Siroux is an architect known for designing the Central Campus complex.
  • C. Hyacinthe Gariel
    Hyacinthe Gariel was a 19th-century French engineer best known for designing the original Pont de l’Alma in Paris.
  • D. Arnaud
    Arnaud is a small commune located in Haiti’s Nippes Department.
  • E. Firmin
    Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
  • 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: Calixte
Triple: [Calixto, etymologicalRelation, Calixte]
Generated description
Calixte is a given name of Latin origin, commonly used in French-speaking regions and derived from the same root as Calixto.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Calixte
Target entity description: Calixte is a given name of Latin origin, commonly used in French-speaking regions and derived from the same root as Calixto.
  • A. Clément
    Clément is a French given name, equivalent to Clement in English, commonly used for males.
  • B. Maxime Siroux
    Maxime Siroux is an architect known for designing the Central Campus complex.
  • C. Hyacinthe Gariel
    Hyacinthe Gariel was a 19th-century French engineer best known for designing the original Pont de l’Alma in Paris.
  • D. Arnaud
    Arnaud is a small commune located in Haiti’s Nippes Department.
  • E. Firmin
    Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d23d7300819095971560759cf456 completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71cc82110819095fb77eb964d23bd completed April 9, 2026, 3:28 a.m.
NEDg Description generation batch_69d73180d90481908f1b4768230edd36 completed April 9, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69d7326b14988190bff33dc01e690707 completed April 9, 2026, 5 a.m.
Created at: April 6, 2026, 11:28 a.m.