Triple

T13850030
Position Surface form Disambiguated ID Type / Status
Subject Caterina Murino E332909 entity
Predicate givenName P17 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: [Caterina Murino, givenName, Caterina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caterina
Context triple: [Caterina Murino, givenName, 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02d8fb788190baef7537be2baecb completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd54f748d481909661deb151da34c1 completed May 8, 2026, 3:13 a.m.
Created at: April 9, 2026, 10:14 p.m.