Triple

T13687881
Position Surface form Disambiguated ID Type / Status
Subject Caterinella E328179 entity
Predicate relatedName P3889 FINISHED
Object Caterina 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: Caterina | Statement: [Caterinella, relatedName, Caterina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caterina
Context triple: [Caterinella, relatedName, Caterina]
  • A. Caterina chosen
    Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
  • B. Caterina Tezio
    Caterina Tezio was the wife of renowned Italian Baroque sculptor and architect Gian Lorenzo Bernini.
  • C. Benedetta
    Benedetta is an Italian feminine given name, equivalent to "Benedicta" and commonly used in Italy and other Italian-speaking communities.
  • D. Giovanna
    Giovanna is an Italian feminine given name equivalent to English "Jane," commonly used in Italy and among Italian-speaking communities.
  • E. Giovannina
    Giovannina is an Italian feminine given name, typically used as a diminutive or affectionate form of Giovanna.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc670968881908e2b4fdf656c7285 completed April 12, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1b661e4819087bac0cd84489baa completed May 6, 2026, 8:16 p.m.
Created at: April 9, 2026, 9:53 p.m.