Triple
T718528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sudan |
E14363
|
entity |
| Predicate | largestCity |
P235
|
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: [Sudan, largestCity, Khartoum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khartoum Context triple: [Sudan, largestCity, 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.
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.
-
C.
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.
-
D.
Port Sudan
Port Sudan is Sudan’s main seaport on the Red Sea, serving as the country’s primary hub for maritime trade and transport.
-
E.
Khartoum International Airport
Khartoum International Airport is the main international gateway and busiest airport serving Sudan’s capital city, Khartoum.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58d4c3c8190ad4527d14bca5e6e |
completed | March 1, 2026, 8:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a67ef6179c81908e72e3d03b61cca4 |
completed | March 3, 2026, 6:25 a.m. |
Created at: March 1, 2026, 7:37 p.m.