Triple

T7940176
Position Surface form Disambiguated ID Type / Status
Subject Christopher Lloyd E184369 entity
Predicate name P16 FINISHED
Object Christopher Lloyd E184369 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: Christopher Lloyd | Statement: [Christopher Lloyd, name, Christopher Lloyd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christopher Lloyd
Context triple: [Christopher Lloyd, name, Christopher Lloyd]
  • A. Christopher Lloyd chosen
    Christopher Lloyd is an American actor best known for his eccentric and memorable roles in film and television, including the time-traveling scientist Doc Brown in the "Back to the Future" trilogy.
  • B. Christopher Lloyd
    Christopher Lloyd is an American television producer and writer best known for co-creating the hit sitcom Modern Family and his work on series like Frasier.
  • C. Jonathan Hyde
    Jonathan Hyde is an English-Australian actor known for his roles in films like "Titanic," "Jumanji," and "The Mummy," as well as extensive work in television, theatre, and voice acting.
  • D. Richard Daniels
    Richard Daniels was a silent film actor known for his comedic roles in early 20th-century cinema.
  • E. Hugh Lloyd
    Hugh Lloyd was a British character actor and comedian best known for his work in mid-20th-century film and television, particularly in comic roles.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b0ac8bc8190b4e4f79b15c316b3 completed March 31, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe019a094819082baecdcb007c84f completed March 31, 2026, 2:54 p.m.
Created at: March 30, 2026, 5:08 p.m.