Triple

T2990343
Position Surface form Disambiguated ID Type / Status
Subject Jobs E80734 entity
Predicate screenwriter P2831 FINISHED
Object Matt Whiteley E46410 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: Matt Whiteley | Statement: [Jobs, screenwriter, Matt Whiteley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Whiteley
Context triple: [Jobs, screenwriter, Matt Whiteley]
  • A. Matt Whiteley chosen
    Matt Whiteley is a screenwriter best known for writing the biographical drama film "Jobs" about Apple co-founder Steve Jobs.
  • B. Derek Twigg
    Derek Twigg is a British Labour Party politician and Member of Parliament who has held several junior ministerial roles in UK government.
  • 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. Iain Farrington
    Iain Farrington is a British pianist, organist, composer, and arranger known for his versatile work across classical and contemporary music, including high-profile national events.
  • E. Jon Whiteley
    Jon Whiteley was a Scottish child actor of the 1950s who gained prominence for his acclaimed film performances, including one that earned him an Academy Juvenile Award.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99de55208190bc56ecbe08638e5a completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b10900bf2481908b7742604c6d75e9 completed March 11, 2026, 6:17 a.m.
Created at: March 8, 2026, 2:59 p.m.