Triple

T21619710
Position Surface form Disambiguated ID Type / Status
Subject Simon Richard D'Arcy E533542 entity
Predicate portrayed P1668 FINISHED
Object Tom Pullings 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: Tom Pullings | Statement: [Simon Richard D'Arcy, portrayed, Tom Pullings]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Pullings
Context triple: [Simon Richard D'Arcy, portrayed, Tom Pullings]
  • A. Tom Pullings chosen
    Tom Pullings is a fictional Royal Navy officer and close protégé of Captain Jack Aubrey in Patrick O’Brian’s Aubrey–Maturin historical naval novels.
  • B. Steven Pemberton
    Steven Pemberton is a British computer scientist and software engineer known for his work on programming languages, web standards, and contributions to the development of ABC and early Python influences.
  • C. Sam Pilling
    Sam Pilling is a British director known for his visually inventive and narrative-driven music videos for prominent contemporary artists.
  • D. Stephen Bull
    Stephen Bull is a distinguished member of the Bull family, recognized for his prominence and contributions associated with this lineage.
  • E. Phil Woolpert
    Phil Woolpert was a prominent American college basketball coach best known for leading the University of San Francisco to multiple national championships in the 1950s.
  • 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_69e0c464fba881908d0ff2ac80511ce1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef3bad094c8190879d4aef7988254a completed April 27, 2026, 10:34 a.m.
Created at: April 16, 2026, 6:34 p.m.