Triple

T25027831
Position Surface form Disambiguated ID Type / Status
Subject Israeli law E626756 entity
Predicate codifiesArea P157912 FINISHED
Object criminal law 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: criminal law | Statement: [Israeli law, codifiesArea, criminal law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: codifiesArea
Context triple: [Israeli law, codifiesArea, criminal law]
  • A. codifiesArea chosen
    Indicates that something formally defines or specifies the rules, structure, or characteristics of a particular area or domain.
  • B. regulatesArea
    Indicates that one entity exercises control or governance over the spatial extent, scope, or domain of another entity.
  • C. codifiedIn
    Indicates that something is formally recorded, defined, or established within a specific document, code, or legal/institutional text.
  • D. regulatedArea
    Indicates that an area is subject to specific rules, controls, or restrictions imposed by an authority.
  • E. codifiedThrough
    Indicates that something is formally established, expressed, or made authoritative by means of a specific codification process, document, or legal/institutional mechanism.
  • 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_69e2ff28ee3881909c626af002457a4a completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f464b4c9b0819085daa00c7c3b8b76 completed May 1, 2026, 8:30 a.m.
PD Predicate disambiguation batch_69f45cfb53f4819099bba48c5057e787 completed May 1, 2026, 7:57 a.m.
Created at: April 18, 2026, 6:07 a.m.