Triple

T12492709
Position Surface form Disambiguated ID Type / Status
Subject Central Equatoria State E298605 entity
Predicate contains P35 FINISHED
Object Juba E112528 NE 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: Juba | Statement: [Central Equatoria State, contains, Juba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juba
Context triple: [Central Equatoria State, contains, Juba]
  • A. Juba chosen
    Juba is the capital and largest city of South Sudan, serving as its political, economic, and administrative center.
  • B. Juba
    Juba is a character in Joseph Addison’s tragedy "Cato," depicted as a noble Numidian prince whose honor and virtue contrast with the corruption of Rome.
  • C. Khartoum
    Khartoum is the capital and largest city of Sudan, located at the confluence of the Blue and White Nile rivers and serving as a major political, economic, and cultural center in the region.
  • D. Sennar city
    Sennar city is an urban center in southeastern Sudan historically known as the capital of the Funj Sultanate and now an important town on the Blue Nile.
  • E. Omdurman
    Omdurman is a major city in Sudan, historically significant as a cultural and commercial center and effectively forming part of the country’s greater capital area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de3076c81909640c982d520ca6b completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556e9180819084ddb984754b0b54 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 9:56 p.m.