Triple

T1822385
Position Surface form Disambiguated ID Type / Status
Subject Francine Houben E40569 entity
Predicate givenName P17 FINISHED
Object Francine
Francine is a feminine given name used in various cultures, often as a French-influenced variant of the name Frances.
 E204725 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: Francine | Statement: [Francine Houben, givenName, Francine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Francine
Context triple: [Francine Houben, givenName, Francine]
  • A. Zibelle
    Zibelle is a village in eastern Germany, historically part of Lusatia, known in this context as the place where physicist Walther Nernst died.
  • B. Mimi
    Mimi is a common affectionate diminutive or nickname for the given name Marie.
  • C. Wilella
    Wilella is the full given name of American novelist Willa Cather, renowned for her works depicting frontier life on the Great Plains.
  • D. Berta
    Berta is a fictional character in Paulo Coelho’s novel "The Devil and Miss Prym," serving as one of the villagers whose life and choices reflect the book’s central moral and spiritual dilemmas.
  • E. Nettie
    Nettie is a key character in "The Color Purple," known as Celie's beloved, intellectually curious sister whose letters and journey abroad provide hope, education, and spiritual grounding to the story.
  • 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: Francine
Triple: [Francine Houben, givenName, Francine]
Generated description
Francine is a feminine given name used in various cultures, often as a French-influenced variant of the name Frances.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Francine
Target entity description: Francine is a feminine given name used in various cultures, often as a French-influenced variant of the name Frances.
  • A. Zibelle
    Zibelle is a village in eastern Germany, historically part of Lusatia, known in this context as the place where physicist Walther Nernst died.
  • B. Mimi
    Mimi is a common affectionate diminutive or nickname for the given name Marie.
  • C. Wilella
    Wilella is the full given name of American novelist Willa Cather, renowned for her works depicting frontier life on the Great Plains.
  • D. Berta
    Berta is a fictional character in Paulo Coelho’s novel "The Devil and Miss Prym," serving as one of the villagers whose life and choices reflect the book’s central moral and spiritual dilemmas.
  • E. Nettie
    Nettie is a key character in "The Color Purple," known as Celie's beloved, intellectually curious sister whose letters and journey abroad provide hope, education, and spiritual grounding to the story.
  • 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_69a8864526c081908a3a4d74f689e2c5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa662b910c8190b1746730ee09015a completed March 6, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf6722f081908c5368a09d1507ac completed March 8, 2026, 6:26 p.m.
NEDg Description generation batch_69adc0a3fdd88190b0ffa98db1b5cf80 completed March 8, 2026, 6:32 p.m.
NED2 Entity disambiguation (via description) batch_69adc1304a808190a999e71dfa39162a completed March 8, 2026, 6:34 p.m.
Created at: March 4, 2026, 7:32 p.m.