Triple

T9325019
Position Surface form Disambiguated ID Type / Status
Subject juvenile courts E224363 entity
Predicate transferDecisionBasedOn P9044 FINISHED
Object seriousness of offense 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: seriousness of offense | Statement: [juvenile courts, transferDecisionBasedOn, seriousness of offense]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: transferDecisionBasedOn
Context triple: [juvenile courts, transferDecisionBasedOn, seriousness of offense]
  • A. decidesOn
    Indicates that an agent makes a choice or determination regarding a particular option, issue, or course of action.
  • B. makesDecisionBy chosen
    Indicates that one entity determines or chooses an outcome, course of action, or judgment by means of another entity, method, or process.
  • C. decisionPointFor
    Indicates a point in a process or workflow at which a choice must be made that determines which subsequent path or outcome will follow.
  • D. decides
    Indicates that an entity makes a choice or determination between options, often resolving uncertainty or selecting a course of action.
  • E. decisionDirection
    Indicates the orientation or course (e.g., choice, stance, or path) that a decision takes relative to available options or influencing factors.
  • 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_69ca8426d48481909596360f7791c7dd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd36f77c808190aa5489c4305fd67d completed April 1, 2026, 3:17 p.m.
PD Predicate disambiguation batch_69cc7a643924819097f01144734901cf completed April 1, 2026, 1:52 a.m.
Created at: March 30, 2026, 7:38 p.m.