Triple

T21106424
Position Surface form Disambiguated ID Type / Status
Subject Robert Day E520055 entity
Predicate hasWorkedWith P9615 FINISHED
Object Christopher Lee 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: Christopher Lee | Statement: [Robert Day, hasWorkedWith, Christopher Lee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christopher Lee
Context triple: [Robert Day, hasWorkedWith, Christopher Lee]
  • A. Christopher Lee chosen
    Christopher Lee was an English actor renowned for his deep voice and imposing presence, best known for iconic roles such as Count Dracula in Hammer Horror films and Saruman in "The Lord of the Rings" trilogy.
  • B. Christopher Lee
    Christopher Lee is an American chef known for his influential work in contemporary Californian cuisine and leadership roles at acclaimed restaurants.
  • C. Peter Cushing
    Peter Cushing was an English actor best known for his roles in classic Hammer horror films and as Grand Moff Tarkin in Star Wars.
  • D. Ian Menzies
    Ian Menzies is a notable individual who shares the Menzies surname, recognized as a distinguished bearer of that family name.
  • E. Michael Ironside
    Michael Ironside is a Canadian actor known for his intense, often villainous roles in science fiction and action films such as "Total Recall," "Starship Troopers," and "Top Gun."
  • 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_69e0b509a318819092fbbcb21d1fe603 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e71b62301c819082cfc6cb3cd11c8c completed April 21, 2026, 6:38 a.m.
Created at: April 16, 2026, 2:53 p.m.