Triple
T21571064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Nimba |
E532283
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Nimba Range |
—
|
NE NERFINISHED |
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: Nimba Range | Statement: [Mount Nimba, partOf, Nimba Range]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nimba Range Context triple: [Mount Nimba, partOf, Nimba Range]
-
A.
Akwapim-Togo Range
The Akwapim-Togo Range is a chain of hills and mountains in southeastern Ghana extending into Togo, known for its scenic landscapes, biodiversity, and role as a natural boundary in the region.
-
B.
Nafusa Mountains
The Nafusa Mountains are a rugged mountain range in northwestern Libya, known for their Berber communities, historical resistance movements, and strategic position overlooking the Tripolitanian plain.
-
C.
Guinea Highlands
chosen
The Guinea Highlands is a mountainous region in West Africa known for its rich mineral resources and as the headwaters of several major rivers, including the Niger.
-
D.
Guinean Loma
Guinean Loma is a regional variety of the Loma language spoken primarily in parts of Guinea.
-
E.
Nuba Mountains
The Nuba Mountains are a rugged, ethnically diverse region in central Sudan known for its long history of conflict, cultural richness, and strategic importance.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eee9cc5c448190887a836f577d01ba |
completed | April 27, 2026, 4:45 a.m. |
Created at: April 16, 2026, 6:30 p.m.