Triple

T3692196
Position Surface form Disambiguated ID Type / Status
Subject Snowpiercer (US distribution) E78367 entity
Predicate stars P1956 FINISHED
Object Jamie Bell E64205 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: Jamie Bell | Statement: [Snowpiercer (US distribution), stars, Jamie Bell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jamie Bell
Context triple: [Snowpiercer (US distribution), stars, Jamie Bell]
  • A. Jamie Bell chosen
    Jamie Bell is an English actor best known for his breakthrough role in the film "Billy Elliot" and subsequent work in movies such as "King Kong," "Snowpiercer," and "Rocketman."
  • B. Katherine Hoult
    Katherine Hoult is known as the spouse of Richard Mather.
  • C. Dakota Fanning
    Dakota Fanning is an American actress who rose to fame as a child star in films like "I Am Sam" and has since built a diverse career in both mainstream and independent cinema.
  • D. Abbie Cornish
    Abbie Cornish is an Australian actress known for her critically acclaimed performances in films such as "Bright Star," "Somersault," and "Sucker Punch," as well as her work in television.
  • E. Anya Taylor-Joy
    Anya Taylor-Joy is an award-winning actress known for her breakout role in "The Queen's Gambit" and performances in films such as "The Witch," "Split," and "Last Night in Soho."
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4e783a88190b2837a68b8723a25 completed March 8, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3cd64c4819098f9f93a8d2efdf7 completed March 14, 2026, 2:11 a.m.
Created at: March 8, 2026, 3:26 p.m.