Triple

T3269064
Position Surface form Disambiguated ID Type / Status
Subject Carine E68597 entity
Predicate hasRelatedName P3889 FINISHED
Object Catharina
Catharina is a feminine given name of Latin origin, commonly used in various European countries as a form of Catherine.
 E154483 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: Catharina | Statement: [Carine, hasRelatedName, Catharina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Catharina
Context triple: [Carine, hasRelatedName, Catharina]
  • A. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • B. Catharina Hent
    Catharina Hent was the wife of Dutch statesman and post–World War II prime minister Willem Drees.
  • C. 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.
  • D. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • E. Béatrix
    Béatrix is a novel by Honoré de Balzac that forms part of his larger La Comédie humaine cycle, depicting the complexities of love and society in 19th-century France.
  • 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: Catharina
Triple: [Carine, hasRelatedName, Catharina]
Generated description
Catharina is a feminine given name of Latin origin, commonly used in various European countries as a form of Catherine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Catharina
Target entity description: Catharina is a feminine given name of Latin origin, commonly used in various European countries as a form of Catherine.
  • A. Ricarda
    Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
  • B. Catharina Hent chosen
    Catharina Hent was the wife of Dutch statesman and post–World War II prime minister Willem Drees.
  • C. 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.
  • D. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • E. Béatrix
    Béatrix is a novel by Honoré de Balzac that forms part of his larger La Comédie humaine cycle, depicting the complexities of love and society in 19th-century France.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafd0eddc8190834a64f6b8e8e9f9 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a698ab08190b558c4ff3f9b27fc completed March 12, 2026, 7:56 p.m.
NEDg Description generation batch_69b31e26b7088190b845a183d32de8bc completed March 12, 2026, 8:12 p.m.
NED2 Entity disambiguation (via description) batch_69b31e7f8c7081908066d5a1c3bce83e completed March 12, 2026, 8:13 p.m.
Created at: March 8, 2026, 3:09 p.m.