Triple

T3888742
Position Surface form Disambiguated ID Type / Status
Subject Ubangi-Shari E88006 entity
Predicate formerColonialCategory P47818 FINISHED
Object French colony in Africa 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: French colony in Africa | Statement: [Ubangi-Shari, formerColonialCategory, French colony in Africa]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: formerColonialCategory
Context triple: [Ubangi-Shari, formerColonialCategory, French colony in Africa]
  • A. formerColonialEntity chosen
    Indicates that one entity was previously a colony or colonial possession of another entity.
  • B. hasColonialHistoryWith
    Indicates that one entity has a historical relationship of colonization or being colonized involving the other entity.
  • C. hadColonialAdministrationType
    Indicates the specific form or system of colonial governance that was exercised over a territory or population.
  • D. wasColonialPower
    Indicates that one entity historically exercised colonial control or dominance over another entity.
  • E. colonialDesignation
    Indicates that one entity assigns or holds a status, name, or classification for another entity within a colonial or colonially imposed framework.
  • 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_69aed9466d548190939f5217a23ed4ac completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecad4bf081909ae45a69d22468fa completed March 9, 2026, 3:52 p.m.
PD Predicate disambiguation batch_69aee759609c8190985e96ec6d96dedd completed March 9, 2026, 3:29 p.m.
Created at: March 9, 2026, 3:21 p.m.