Triple

T34518291
Position Surface form Disambiguated ID Type / Status
Subject Ewulu E886213 entity
Predicate hasNationalLegalSystem P187565 FINISHED
Object Nigerian 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: Nigerian law | Statement: [Ewulu, hasNationalLegalSystem, Nigerian law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNationalLegalSystem
Context triple: [Ewulu, hasNationalLegalSystem, Nigerian law]
  • A. countryOfLegalSystem
    Indicates the relationship between a legal system and the country in which that legal system is officially established or applied.
  • B. hasStateLawSystem chosen
    Indicates that a jurisdiction or entity operates under or is governed by a particular system of state laws.
  • C. hasExtendedLawSystem
    Indicates that an entity possesses a comprehensive, detailed, and well-developed system of laws or legal regulations.
  • D. usedLegalSystemOf
    Indicates that one entity applied, followed, or operated under the legal system or body of laws belonging to another entity.
  • E. hasLegalSystemType
    Indicates that an entity possesses or is governed by a particular type or form of legal system.
  • 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_69f349ccc290819089d8e82698e53cb6 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69ff136ed2a881908f713401083970d1 completed May 9, 2026, 10:58 a.m.
PD Predicate disambiguation batch_69ff10f9e3448190b6cb6ea5a67713c1 completed May 9, 2026, 10:48 a.m.
Created at: May 1, 2026, 2:01 a.m.