Triple

T8244550
Position Surface form Disambiguated ID Type / Status
Subject Trucks (1997 film) E192817 entity
Predicate relatedWork P37 FINISHED
Object Maximum Overdrive E192813 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: Maximum Overdrive | Statement: [Trucks (1997 film), relatedWork, Maximum Overdrive]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maximum Overdrive
Context triple: [Trucks (1997 film), relatedWork, Maximum Overdrive]
  • A. Maximum Overdrive chosen
    Maximum Overdrive is a 1986 horror-comedy film written and directed by Stephen King, in which machines suddenly become homicidal and terrorize a group of people trapped at a truck stop.
  • B. Overload
    "Overload" is a song featured on the album "All I Want Is You."
  • C. Overload
    "Overload" is a song by the Christian rock band Darkness and Light, likely featuring their characteristic blend of heavy guitar-driven sound and spiritually themed lyrics.
  • D. Overdrive
    Overdrive is an action-packed heist film centered on high-end car thieves, starring Scott Eastwood.
  • E. Full Throttle
    Full Throttle is a horror and dark fantasy short story collection by Joe Hill that showcases his signature blend of suspenseful, character-driven tales.
  • 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_69ca82de7b8c81908d8106f8a53cff9b completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78711f5081909c2f357334491a07 completed March 31, 2026, 7:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd94ec40a8819081655fee94614525 completed April 1, 2026, 9:58 p.m.
Created at: March 30, 2026, 5:47 p.m.