Triple

T11098517
Position Surface form Disambiguated ID Type / Status
Subject Feliz E262439 entity
Predicate hasCognate P2525 FINISHED
Object Felice E878728 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: Felice | Statement: [Feliz, hasCognate, Felice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Felice
Context triple: [Feliz, hasCognate, Felice]
  • A. Felice chosen
    Felice is a comic character from the classic French farce "Il cappello di paglia di Firenze" (The Florentine Straw Hat), typically involved in the play’s intricate misunderstandings and humorous situations.
  • B. Felici
    Felici is an Italian surname associated with figures such as Cardinal Pericle Felici, a prominent 20th-century prelate of the Catholic Church.
  • C. Felix
    Felix is a masculine given name of Latin origin meaning "happy" or "fortunate," borne by numerous historical and contemporary figures.
  • D. Felicio
    Felicio is a given name that functions as a variant form of the name Felix, sharing its Latin roots and connotations of happiness or good fortune.
  • E. Frieda
    Frieda is a 1947 British drama film produced by Michael Balcon that explores post-World War II tensions and prejudice in England.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a0b2890819081c4efc50e995cdd completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f395944c8190bf0f824156f0f370 completed April 19, 2026, 3:24 p.m.
Created at: April 8, 2026, 9:27 p.m.