Triple

T5485833
Position Surface form Disambiguated ID Type / Status
Subject Final Destination film series E123577 entity
Predicate frequentSettingType P64318 FINISHED
Object contemporary American locations LITERAL 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: contemporary American locations | Statement: [Final Destination film series, frequentSettingType, contemporary American locations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: frequentSettingType
Context triple: [Final Destination film series, frequentSettingType, contemporary American locations]
  • A. isFrequently
    Indicates that an action, state, or relationship occurs often or with high regularity between the related entities.
  • B. serviceFrequencyType
    Indicates how often a service occurs or is scheduled within a given time period.
  • C. usesFrequency
    Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
  • D. frequentOccasion
    Indicates that a particular event, situation, or condition occurs repeatedly or commonly over time.
  • E. serviceFrequencyContext
    Indicates the contextual conditions or circumstances under which a service’s frequency is defined, applied, or interpreted.
  • F. None of above. chosen

Provenance (4 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_69bd4648883481909e9775d43300c5fa completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd93e5d0f08190a6cc9fc408b7c5bb completed March 20, 2026, 6:37 p.m.
PD Predicate disambiguation batch_69bd91a73b148190a865243536a4fe76 completed March 20, 2026, 6:27 p.m.
PDg Predicate description generation batch_69bd93e4d2d081908eb75ee22fe72824 completed March 20, 2026, 6:37 p.m.
Created at: March 20, 2026, 2:10 p.m.