Triple

T9018843
Position Surface form Disambiguated ID Type / Status
Subject Josephine E215661 entity
Predicate hasVariant P455 FINISHED
Object Josefine
Josefine is a feminine given name, commonly used in various European countries as a spelling variant of Josephine.
 E774176 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: Josefine | Statement: [Josephine, hasVariant, Josefine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Josefine
Context triple: [Josephine, hasVariant, Josefine]
  • A. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • B. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • C. Josefa
    Josefa is a feminine given name of Spanish origin, historically borne by notable figures such as Mexican independence heroine Josefa Ortiz de Domínguez.
  • D. Therese
    Therese is a feminine given name of French origin, commonly associated with Christian saints and used in various European cultures.
  • E. Bettina
    Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • 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: Josefine
Triple: [Josephine, hasVariant, Josefine]
Generated description
Josefine is a feminine given name, commonly used in various European countries as a spelling variant of Josephine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Josefine
Target entity description: Josefine is a feminine given name, commonly used in various European countries as a spelling variant of Josephine.
  • A. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • B. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • C. Josefa
    Josefa is a feminine given name of Spanish origin, historically borne by notable figures such as Mexican independence heroine Josefa Ortiz de Domínguez.
  • D. Therese
    Therese is a feminine given name of French origin, commonly associated with Christian saints and used in various European cultures.
  • E. Bettina
    Bettina is a feminine given name of Hebrew origin, often considered a diminutive of Elisabeth or Benedetta and used in various European languages.
  • 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_69ca83a38aa88190bf1bb80c4548b5e2 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6a4085848190a6aa440e6307e93d completed April 1, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfeb7117c48190a9dca7bbdabe9e3d completed April 3, 2026, 4:31 p.m.
NEDg Description generation batch_69cfed0af5a8819096223cb8c928296b completed April 3, 2026, 4:38 p.m.
NED2 Entity disambiguation (via description) batch_69cfed7322c48190b82599e63abd523a completed April 3, 2026, 4:40 p.m.
Created at: March 30, 2026, 7:07 p.m.