Triple

T1924632
Position Surface form Disambiguated ID Type / Status
Subject Medical Act 1983 E40800 entity
Predicate authorises P273 FINISHED
Object maintenance of a medical register 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: maintenance of a medical register | Statement: [Medical Act 1983, authorises, maintenance of a medical register]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: authorises
Context triple: [Medical Act 1983, authorises, maintenance of a medical register]
  • A. canAuthorize
    Indicates that one entity has the power or permission to grant approval or official permission for another entity to perform an action or access a resource.
  • B. authorityGranted
    Indicates that one entity has formally given another entity the power, rights, or permission to act or make decisions, typically within a defined scope or context.
  • C. allows chosen
    Indicates that one entity grants permission, capability, or opportunity for another entity to perform an action or be in a certain state.
  • D. usesAuthorityOf
    Indicates that one entity exercises power, rights, or influence derived from or on behalf of another entity’s authority.
  • E. approves
    Indicates that one entity formally accepts, authorizes, or agrees to a proposal, action, or decision made by another entity.
  • 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_69a8864711648190b07bed24ed76258e completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb2359ca0819082b514a34c469b21 completed March 7, 2026, 5:05 a.m.
PD Predicate disambiguation batch_69abafeec6f881909d47acb966683279 completed March 7, 2026, 4:56 a.m.
Created at: March 4, 2026, 7:35 p.m.