Triple

T8958905
Position Surface form Disambiguated ID Type / Status
Subject Joseph Wiseman E213548 entity
Predicate name P16 FINISHED
Object Joseph Wiseman E213548 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: Joseph Wiseman | Statement: [Joseph Wiseman, name, Joseph Wiseman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joseph Wiseman
Context triple: [Joseph Wiseman, name, Joseph Wiseman]
  • A. Joseph Wiseman chosen
    Joseph Wiseman was a Canadian character actor best known for portraying the titular villain in the first James Bond film, "Dr. No."
  • B. Arthur Dorman
    Arthur Dorman was a British industrialist best known as a co-founder of the major steel and engineering firm Dorman Long and Co Ltd, which played a significant role in bridge building and heavy industry.
  • C. Douglas Wick
    Douglas Wick is an American film producer known for acclaimed movies such as "Gladiator," "Working Girl," and "Memoirs of a Geisha."
  • D. George Ward
    George Ward was a British Conservative politician who served in senior government roles during the mid-20th century, including as Minister of Supply.
  • E. Gordon Jennings
    Gordon Jennings was an American special effects artist renowned for his pioneering visual effects work in mid-20th-century Hollywood science fiction and adventure films.
  • 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_69ca8399ad2081909f8fa41d4314c215 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc672b12b48190a9d964f79b96d237 completed April 1, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd09e378c8190bb9f5d78a3b91fe7 completed April 3, 2026, 2:37 p.m.
Created at: March 30, 2026, 7 p.m.