Triple

T1982528
Position Surface form Disambiguated ID Type / Status
Subject Terminator E43058 entity
Predicate hasVideoGameAdaptations P8717 FINISHED
Object yes 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: yes | Statement: [Terminator, hasVideoGameAdaptations, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasVideoGameAdaptations
Context triple: [Terminator, hasVideoGameAdaptations, yes]
  • A. hasMediaFranchise
    Indicates that one entity is part of, or belongs to, a larger media franchise represented by another entity.
  • B. adaptedAs
    Indicates that one work, concept, or entity has been transformed or re-created into another form or medium based on the original.
  • C. videoGame chosen
    Indicates that one entity is a video game associated with, created by, or otherwise related to another entity.
  • D. notableAdaptation
    Indicates that one work is a significant adaptation or reinterpretation of another work.
  • E. hasFictionalUniverseGenre
    Indicates that a fictional universe is associated with a particular genre that characterizes its overall style, themes, or narrative type.
  • F. None of above.

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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb96f932881908bebfc4176fda7c0 completed March 7, 2026, 5:36 a.m.
PD Predicate disambiguation batch_69abb798d288819083132cf14605bd02 completed March 7, 2026, 5:28 a.m.
Created at: March 4, 2026, 7:37 p.m.