Triple
T7060814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamazight |
E164210
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Niger |
E22368
|
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: Niger | Statement: [Tamazight, spokenIn, Niger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niger Context triple: [Tamazight, spokenIn, Niger]
-
A.
Niger
chosen
Niger is a landlocked West African country in the Sahel region, known for its vast desert landscapes, uranium resources, and predominantly rural population.
-
B.
Guinea
Guinea is a West African country on the Atlantic coast known for its rich mineral resources, diverse ethnic groups, and role as a major producer of bauxite.
-
C.
Mali
Mali is a landlocked West African country known for its historic trading cities like Timbuktu, rich Sahelian culture, and significant role in the ancient Mali Empire.
-
D.
Río de Oro
Río de Oro was a former Spanish colonial territory in northwest Africa that later became part of the disputed region of Western Sahara.
-
E.
Ennedi
Ennedi is a remote region in northeastern Chad renowned for its dramatic sandstone massifs, rock arches, and prehistoric rock art.
- 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_69c688796c148190adb2f1596f595f22 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e459de348190912cd5326fb8bee0 |
completed | March 27, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c788af20cc819084542035410aafbd |
completed | March 28, 2026, 7:52 a.m. |
Created at: March 27, 2026, 2:38 p.m.