Triple

T8534509
Position Surface form Disambiguated ID Type / Status
Subject Victorine Haven Putnam E202043 entity
Predicate givenName P17 FINISHED
Object Victorine
Victorine is a feminine given name of Latin origin, derived from "Victor," meaning "victorious" or "conqueror."
 E746001 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: Victorine | Statement: [Victorine Haven Putnam, givenName, Victorine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Victorine
Context triple: [Victorine Haven Putnam, givenName, Victorine]
  • A. Viviane
    Viviane is a legendary enchantress of Arthurian romance, often identified as the Lady of the Lake and known for her role in mentoring and imprisoning the wizard Merlin.
  • B. Delphine
    Delphine is an epistolary novel by Madame de Staël that explores themes of love, social convention, and women's independence in late 18th-century French society.
  • C. Ninon Dolbin
    Ninon Dolbin was the second wife of German-Swiss writer Hermann Hesse, known for supporting and managing aspects of his literary life.
  • D. Marcelle
    Marcelle is a given name, typically a feminine form of Marcel, used in various cultures.
  • E. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • 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: Victorine
Triple: [Victorine Haven Putnam, givenName, Victorine]
Generated description
Victorine is a feminine given name of Latin origin, derived from "Victor," meaning "victorious" or "conqueror."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Victorine
Target entity description: Victorine is a feminine given name of Latin origin, derived from "Victor," meaning "victorious" or "conqueror."
  • A. Viviane
    Viviane is a legendary enchantress of Arthurian romance, often identified as the Lady of the Lake and known for her role in mentoring and imprisoning the wizard Merlin.
  • B. Delphine
    Delphine is an epistolary novel by Madame de Staël that explores themes of love, social convention, and women's independence in late 18th-century French society.
  • C. Ninon Dolbin
    Ninon Dolbin was the second wife of German-Swiss writer Hermann Hesse, known for supporting and managing aspects of his literary life.
  • D. Marcelle
    Marcelle is a given name, typically a feminine form of Marcel, used in various cultures.
  • E. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • 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_69ca832355b08190b8b6a4ab4a4a3554 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6a0ccd4819097b41d0dfb1c5018 completed March 31, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea854e8c881909c62b29d999edde8 completed April 2, 2026, 5:33 p.m.
NEDg Description generation batch_69cea996a5c48190a12ffe8e282d2d9c completed April 2, 2026, 5:38 p.m.
NED2 Entity disambiguation (via description) batch_69ceadb2d52c8190aada1d797753663e completed April 2, 2026, 5:56 p.m.
Created at: March 30, 2026, 6:17 p.m.