Triple

T2758588
Position Surface form Disambiguated ID Type / Status
Subject Stephen Fry E61163 entity
Predicate twitterHandle P2866 FINISHED
Object @stephenfry E61163 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: @stephenfry | Statement: [Stephen Fry, twitterHandle, @stephenfry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: @stephenfry
Context triple: [Stephen Fry, twitterHandle, @stephenfry]
  • A. Stephen Fry chosen
    Stephen Fry is a British actor, comedian, writer, and broadcaster known for his work in television, film, literature, and radio, as well as his wit and public intellectual presence.
  • B. Julian Fry
    Julian Fry was the son of influential British art critic and painter Roger Fry, associated with the Bloomsbury Group.
  • C. Jonathan Cavendish
    Jonathan Cavendish is a British film producer best known for co-founding The Imaginarium Studios and producing acclaimed films such as "Bridget Jones’s Diary" and "Breathe."
  • D. Danny Baker
    Danny Baker is a British broadcaster and writer known for his eclectic radio shows, television presenting, and autobiographical books.
  • E. Russell Brand
    Russell Brand is an English comedian, actor, and author known for his flamboyant, fast-talking style and roles in films such as "Forgetting Sarah Marshall" and "Get Him to the Greek."
  • 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_69ab4b7a85bc819094a349b84beb1f2c completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb8d34f88190a760111fe303cf24 completed March 7, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbe2d9cc81909b041635ae793bc3 completed March 10, 2026, 6:36 a.m.
Created at: March 6, 2026, 9:57 p.m.