Triple
T127230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Africa |
E2576
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Sudan |
E14363
|
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: Sudan | Statement: [North Africa, hasPart, Sudan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sudan Context triple: [North Africa, hasPart, Sudan]
-
A.
Sudan
chosen
Sudan is a large Northeast African country along the Nile River, known for its diverse cultures, ancient Nubian history, and a modern history marked by civil conflict and the secession of South Sudan.
-
B.
Nubia
Nubia is a historic region along the Nile in southern Egypt and northern Sudan, renowned for its ancient civilizations, archaeological sites, and monumental temples.
-
C.
Chad
Chad is a landlocked country in north-central Africa known for its ethnic and linguistic diversity, vast desert regions, and significant oil reserves.
-
D.
Somalia
Somalia is a country in the Horn of Africa known for its long coastline along the Indian Ocean, predominantly arid climate, and complex modern history marked by civil conflict and efforts at state reconstruction.
-
E.
Niger
Niger is a landlocked West African country in the Sahel region, known for its vast desert landscapes, uranium resources, and predominantly rural population.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25761e9248190a7205bfc36cb5c45 |
completed | Feb. 28, 2026, 2:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3914a01d8819083604dfc0844c0e1 |
completed | March 1, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.