Triple

T14653383
Position Surface form Disambiguated ID Type / Status
Subject Ghoulies E344047 entity
Predicate character P662 FINISHED
Object Jonathan Graves E1111996 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: Jonathan Graves | Statement: [Ghoulies, character, Jonathan Graves]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonathan Graves
Context triple: [Ghoulies, character, Jonathan Graves]
  • A. Jonathan Graves chosen
    Jonathan Graves is the protagonist of the 1985 horror-comedy film "Ghoulies," a young man who unwittingly unleashes demonic creatures while dabbling in occult rituals.
  • B. Randal Graves
    Randal Graves is a sarcastic, irreverent video store clerk and one of the central comedic antiheroes in Kevin Smith’s Clerks franchise.
  • C. John Stonehouse
    John Stonehouse was a British Labour politician and former cabinet minister best known for faking his own death in 1974 in an attempt to escape financial and legal troubles.
  • D. Ralph Graves
    Ralph Graves was an American film actor prominent in the silent and early sound eras, often appearing in action and drama films of the 1920s and 1930s.
  • E. John Grandy
    John Grandy was a senior Royal Air Force officer who rose to become a leading commander of British fighter forces during and after the Second World War.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb518f7dc8190877997ea4cd3eed2 completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde17283608190a8351b366cac5e4f completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:27 a.m.