Triple
T18259207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basil Dearden |
E437301
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Khartoum |
—
|
NE NERFINISHED |
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: [Basil Dearden, notableWork, Khartoum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khartoum Context triple: [Basil Dearden, notableWork, 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 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.
Juba
Juba is the capital and largest city of South Sudan, serving as its political, economic, and administrative center.
-
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 (2 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd89899c8190b8b652c4f61aa5cf |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:34 a.m.