Triple
T9066763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Makuria |
E217263
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Dongola |
E138678
|
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: Dongola | Statement: [Kingdom of Makuria, capital, Dongola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dongola Context triple: [Kingdom of Makuria, capital, Dongola]
-
A.
Dongola
chosen
Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
-
B.
Safaga
Safaga is a coastal town and port on Egypt’s Red Sea coast known for its diving sites, black sand beaches, and therapeutic tourism.
-
C.
Kenuzi-Dongola
Kenuzi-Dongola is a Nubian language of the Eastern Sudanic branch spoken primarily along the Nile in southern Egypt and northern Sudan.
-
D.
Ras Lanuf
Ras Lanuf is a major oil port and industrial town on Libya’s Mediterranean coast, known for its large refinery and strategic role in the country’s petroleum exports.
-
E.
Adigrat
Adigrat is a major town in northern Ethiopia known as a commercial and administrative center near the Eritrean border.
- 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_69ca83d5a7f48190b16c1e59bd43ede0 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc94bde9c08190a4f568fbccc3c3e9 |
completed | April 1, 2026, 3:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d04774f4488190b4212ac516910251 |
completed | April 3, 2026, 11:04 p.m. |
Created at: March 30, 2026, 7:11 p.m.