Triple

T7245349
Position Surface form Disambiguated ID Type / Status
Subject Criminal Codes of the Union Republics E156456 entity
Predicate includesOffencesAgainst P67290 FINISHED
Object state security 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: state security | Statement: [Criminal Codes of the Union Republics, includesOffencesAgainst, state security]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: includesOffencesAgainst
Context triple: [Criminal Codes of the Union Republics, includesOffencesAgainst, state security]
  • A. includesOffenseType chosen
    Indicates that one entity contains, specifies, or is associated with a particular category or type of offense.
  • B. includesCrimesAgainstSociety
    Indicates that the referenced entity involves, encompasses, or is associated with offenses classified as crimes against society (such as public order, moral, or regulatory violations).
  • C. definesOffence
    Indicates that one entity specifies or establishes the nature, elements, or scope of an offence associated with another entity.
  • D. supportsMultipleOffensesPerIncident
    Indicates that a single incident can be associated with, or give rise to, more than one distinct offense.
  • E. consideredCriminalBy
    Indicates that one party regards or classifies another party as a criminal according to its own laws, rules, or judgments.
  • 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_69c68827b5e481908dc05e145b2c92d4 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea596fdc8190b2115363f1033441 completed March 27, 2026, 8:36 p.m.
PD Predicate disambiguation batch_69c6e7666ffc81908bf643d8257e6337 completed March 27, 2026, 8:24 p.m.
Created at: March 27, 2026, 2:56 p.m.