Triple

T12378367
Position Surface form Disambiguated ID Type / Status
Subject Marcelline Hemingway E295682 entity
Predicate givenName P17 FINISHED
Object Marcelline
Marcelline is a feminine given name of Latin origin, derived from "Marcellinus" and related to "Marcella," often associated with early Christian saints.
 E740092 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: Marcelline | Statement: [Marcelline Hemingway, givenName, Marcelline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marcelline
Context triple: [Marcelline Hemingway, givenName, Marcelline]
  • A. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • B. Marcelle
    Marcelle is a given name, typically a feminine form of Marcel, used in various cultures.
  • C. Armande
    Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
  • D. Noémie
    Noémie is a French given name, equivalent to Naomi, commonly used for girls in Francophone countries.
  • E. Bénédicte
    Bénédicte is the given name of Louise Bénédicte de Bourbon, a French noblewoman of the House of Bourbon.
  • 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: Marcelline
Triple: [Marcelline Hemingway, givenName, Marcelline]
Generated description
Marcelline is a feminine given name of Latin origin, derived from "Marcellinus" and related to "Marcella," often associated with early Christian saints.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marcelline
Target entity description: Marcelline is a feminine given name of Latin origin, derived from "Marcellinus" and related to "Marcella," often associated with early Christian saints.
  • A. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • B. Marcelle chosen
    Marcelle is a given name, typically a feminine form of Marcel, used in various cultures.
  • C. Armande
    Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
  • D. Noémie
    Noémie is a French given name, equivalent to Naomi, commonly used for girls in Francophone countries.
  • E. Bénédicte
    Bénédicte is the given name of Louise Bénédicte de Bourbon, a French noblewoman of the House of Bourbon.
  • F. None of above.

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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fb8d6c081909e8bbbd52c73f29c completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac3c9f081909cd55f966ab6b465 completed May 2, 2026, 4:48 p.m.
NEDg Description generation batch_69f62c57a26081908d6903906f6e04f0 completed May 2, 2026, 4:54 p.m.
NED2 Entity disambiguation (via description) batch_69f62d0c2568819083e66c8ae484d30d completed May 2, 2026, 4:57 p.m.
Created at: April 8, 2026, 9:54 p.m.