Triple

T14723011
Position Surface form Disambiguated ID Type / Status
Subject Into the Storm (2014 film) E345861 entity
Predicate stars P1956 FINISHED
Object Jeremy Sumpter E670897 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: Jeremy Sumpter | Statement: [Into the Storm (2014 film), stars, Jeremy Sumpter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeremy Sumpter
Context triple: [Into the Storm (2014 film), stars, Jeremy Sumpter]
  • A. Jeremy Sumpter chosen
    Jeremy Sumpter is an American actor best known for playing the title role in the 2003 film adaptation of "Peter Pan."
  • B. Alex Hibbert
    Alex Hibbert is an American actor best known for his acclaimed performance as young Chiron in the Oscar-winning film "Moonlight."
  • C. Jesse Hartley
    Jesse Hartley was a 19th-century British civil engineer and dock architect best known for designing and overseeing the construction of Liverpool’s pioneering dock systems.
  • D. Christopher Henderson
    Christopher Henderson is a fictional high-ranking counterterrorism operative and former mentor to Jack Bauer in the television series "24."
  • E. Adrian Lester
    Adrian Lester is a British actor and director acclaimed for his powerful stage performances in both classical and contemporary theatre, as well as notable roles in film and television.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec25e9a14819081fa06fc601f295d completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0ce3d1d88190951e88bef88db500 completed May 8, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:29 a.m.