Triple

T20325942
Position Surface form Disambiguated ID Type / Status
Subject Francia Raisa E492337 entity
Predicate hasTwitterUsername P2943 FINISHED
Object franciaraisa NE NERFINISHED

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: franciaraisa | Statement: [Francia Raisa, hasTwitterUsername, franciaraisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: franciaraisa
Context triple: [Francia Raisa, hasTwitterUsername, franciaraisa]
  • A. franciaraisa chosen
    Francia Raisa is an American actress best known for her roles in "The Secret Life of the American Teenager" and "Grown-ish."
  • B. Franzese
    Franzese is an Italian surname borne by various notable individuals in fields such as entertainment and organized crime.
  • C. Fransat
    Fransat is a French free-to-air satellite television platform that provides access to the national digital terrestrial TV channels across France.
  • D. FR-EE
    FR-EE is an international architecture and design firm known for its innovative, futuristic projects and urban-scale developments led by Mexican architect Fernando Romero.
  • E. Fran
    Fran is a common shortened given name, typically used as a diminutive of Frances or Francis.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4a0134081909113563e1c3ba68a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6778f20288190b1862d6be61bfb67 completed April 20, 2026, 6:59 p.m.
Created at: April 16, 2026, 11:21 a.m.