Triple

T15418368
Position Surface form Disambiguated ID Type / Status
Subject Suge Knight E369308 entity
Predicate incidentContext P2919 FINISHED
Object 2015 hit-and-run at a film set for Straight Outta Compton 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: 2015 hit-and-run at a film set for Straight Outta Compton | Statement: [Suge Knight, incidentContext, 2015 hit-and-run at a film set for Straight Outta Compton]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: incidentContext
Context triple: [Suge Knight, incidentContext, 2015 hit-and-run at a film set for Straight Outta Compton]
  • A. incidentWith
    Indicates that one entity is involved in, affected by, or associated with a particular incident or event together with another entity.
  • B. incidentCharacterization
    Indicates how an incident is classified or characterized in terms of its nature, attributes, or type.
  • C. context
    Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
  • D. contextOf chosen
    Indicates that one entity provides the situational, informational, or environmental background within which another entity exists, occurs, or is interpreted.
  • E. attackContext
    Indicates the situational circumstances, conditions, or factors surrounding an attack event or action.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ebce4f48190ba282ecb4fb2f6fa completed April 16, 2026, 1:43 a.m.
PD Predicate disambiguation batch_69ded27f45548190a6d2b1b85cb47444 completed April 14, 2026, 11:49 p.m.
Created at: April 10, 2026, 3:20 a.m.