Triple
T101581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigeria |
E2050
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Abuja |
E9148
|
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: Abuja | Statement: [Nigeria, containsCity, Abuja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abuja Context triple: [Nigeria, containsCity, Abuja]
-
A.
Abuja
chosen
Abuja is a planned city in central Nigeria that serves as the country’s political and administrative center.
-
B.
Lagos
Lagos is a major coastal megacity in southwestern Nigeria, known as the country’s economic hub and one of Africa’s most populous and vibrant urban centers.
-
C.
Nairobi
Nairobi is the capital and largest city of Kenya, serving as a major political, economic, and cultural hub in East Africa.
-
D.
Khartoum
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.
-
E.
Nigeria
Nigeria is a populous West African country known for its diverse ethnic groups, rich cultural heritage, and status as Africa’s largest economy and oil producer.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a256a8b6d0819083838a9708759407 |
completed | Feb. 28, 2026, 2:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a27c030ddc8190af2ebb672237bf18 |
completed | Feb. 28, 2026, 5:24 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.