Triple
T4959267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Souss-Massa |
E111363
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Inezgane |
E239429
|
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: Inezgane | Statement: [Souss-Massa, containsCity, Inezgane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inezgane Context triple: [Souss-Massa, containsCity, Inezgane]
-
A.
Inezgane
chosen
Inezgane is a town in southwestern Morocco known as a major transport hub and commercial center just inland from the coastal city of Agadir.
-
B.
Makaziwe
Makaziwe is a South African academic and businesswoman best known as the daughter of Nelson Mandela.
-
C.
Mabalako
Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
-
D.
Esigodini
Esigodini is a small town in southwestern Zimbabwe known for its agricultural surroundings and role as a local service and transport hub.
-
E.
Ndungane
Ndungane is a surname most notably associated with South African Anglican archbishop and social justice advocate Njongonkulu Ndungane.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71d957cc8190b82fdd1ca61924bf |
completed | March 20, 2026, 4:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81e4ccc4819090223633fdb04eee |
completed | March 21, 2026, 11:32 a.m. |
Created at: March 20, 2026, 1:32 p.m.