Triple

T12851627
Position Surface form Disambiguated ID Type / Status
Subject Turco-Egyptian Sudan E307335 entity
Predicate areaIncludes P36978 FINISHED
Object Khartoum E7633 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: Khartoum | Statement: [Turco-Egyptian Sudan, areaIncludes, Khartoum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khartoum
Context triple: [Turco-Egyptian Sudan, areaIncludes, Khartoum]
  • A. Khartoum chosen
    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.
  • B. Juba
    Juba is the capital and largest city of South Sudan, serving as its political, economic, and administrative center.
  • C. 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.
  • D. 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.
  • E. Khartoum North
    Khartoum North is a major city in Sudan forming part of the tri-city metropolitan area with Khartoum and Omdurman, known as an important industrial and commercial center.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97020eacc81909357b3398d17dc49 completed April 10, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e260b824819083e90333827d0833 completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 5:36 p.m.