Triple

T821303
Position Surface form Disambiguated ID Type / Status
Subject Catharina Bolnes E17751 entity
Predicate givenName P17 FINISHED
Object Catharina E64628 NE FINISHED

How this triple was built (2 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: [Catharina Bolnes, givenName, Catharina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catharina
Context triple: [Catharina Bolnes, givenName, Catharina]
  • A. 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.
  • B. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • C. Caterina chosen
    Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
  • D. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • E. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab7aea38819092a0860ec6e2a033 completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2a0906408190bd54e6308af30631 completed March 7, 2026, 1:37 p.m.
Created at: March 1, 2026, 7:38 p.m.