Triple

T27537369
Position Surface form Disambiguated ID Type / Status
Subject Ndzuwani E695131 entity
Predicate hasLegalSystemOfGoverningCountry P65627 FINISHED
Object mixed civil and Islamic 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: mixed civil and Islamic law | Statement: [Ndzuwani, hasLegalSystemOfGoverningCountry, mixed civil and Islamic law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLegalSystemOfGoverningCountry
Context triple: [Ndzuwani, hasLegalSystemOfGoverningCountry, mixed civil and Islamic law]
  • A. countryOfLegalSystem
    Indicates the relationship between a legal system and the country in which that legal system is officially established or applied.
  • B. governedByLegalRegime
    Indicates that an entity is subject to, regulated by, or operating under a specific legal framework or set of legal rules.
  • C. hasLegalSystemType chosen
    Indicates that an entity possesses or is governed by a particular type or form of legal system.
  • D. governingSystemCountry
    Indicates that a particular system of governance is the ruling or official governing system used by a given country.
  • E. usedLegalSystemOf
    Indicates that one entity applied, followed, or operated under the legal system or body of laws belonging to 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_69ef538608b081908b9f659bb09d5e0f completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f6e6029a10819098ff21f58079e70e completed May 3, 2026, 6:06 a.m.
PD Predicate disambiguation batch_69f6e3d5e8188190b1e1c2e5d1b77031 completed May 3, 2026, 5:57 a.m.
Created at: April 27, 2026, 1:29 p.m.