Triple

T3323162
Position Surface form Disambiguated ID Type / Status
Subject On Crimes and Punishments E69844 entity
Predicate aimOfPunishment P47279 FINISHED
Object prevention of crime 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: prevention of crime | Statement: [On Crimes and Punishments, aimOfPunishment, prevention of crime]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: aimOfPunishment
Context triple: [On Crimes and Punishments, aimOfPunishment, prevention of crime]
  • A. punishedBy
    Indicates that an entity receives punishment administered by another entity.
  • B. aimOfCondemnation
    Indicates that an act of condemnation is directed toward a particular target or objective.
  • C. reasonForConviction
    Indicates the specific offense or legal basis for which an individual was found guilty or convicted.
  • D. punishmentLocation
    Indicates the place or setting where a punishment is carried out or imposed.
  • E. hasPunishment
    Indicates that an entity is subject to a specified penalty, sanction, or adverse consequence as a result of some action, condition, or rule.
  • 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_69ad85a1829881908942c14075644d0d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb13e6c288190805f8abcd3acc906 completed March 8, 2026, 5:26 p.m.
PD Predicate disambiguation batch_69ada42a19348190a3862ce02451f4aa completed March 8, 2026, 4:30 p.m.
PDg Predicate description generation batch_69ada52716ec81908e89688a81039394 completed March 8, 2026, 4:34 p.m.
Created at: March 8, 2026, 3:11 p.m.