Triple

T910385
Position Surface form Disambiguated ID Type / Status
Subject Richard E19643 entity
Predicate hasFeminineForm P1613 FINISHED
Object Ricarda
Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
 E119001 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: Ricarda | Statement: [Richard, hasFeminineForm, Ricarda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ricarda
Context triple: [Richard, hasFeminineForm, Ricarda]
  • A. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • B. Gertrudis
    Gertrudis is a passionate and rebellious sister in "Like Water for Chocolate" whose fiery nature and unconventional choices challenge her family's strict traditions.
  • C. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • D. Caterina
    Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
  • E. Dorothee
    Dorothee is a feminine given name, commonly used in German- and French-speaking countries, that is a variant of the name Dorothea.
  • 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: Ricarda
Triple: [Richard, hasFeminineForm, Ricarda]
Generated description
Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ricarda
Target entity description: Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • A. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • B. Gertrudis
    Gertrudis is a passionate and rebellious sister in "Like Water for Chocolate" whose fiery nature and unconventional choices challenge her family's strict traditions.
  • C. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • D. Caterina
    Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
  • E. Dorothee
    Dorothee is a feminine given name, commonly used in German- and French-speaking countries, that is a variant of the name Dorothea.
  • 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_69a4939f91a08190ba68c2c81eab90fe completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2dca5208190bc9f17cd9dd6a98f completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3b9b7eb88190b7fa4f9dbcc73d64 completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3c5009a4819096a0473589235f4f completed March 7, 2026, 2:55 p.m.
NED2 Entity disambiguation (via description) batch_69ac3caa8ca88190994c7158d0e91f87 completed March 7, 2026, 2:56 p.m.
Created at: March 1, 2026, 7:39 p.m.