Triple
T3117430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rwenzori Mountains |
E65095
|
entity |
| Predicate | rankByElevationInAfrica |
P39147
|
FINISHED |
| Object | third-highest mountain range in Africa |
—
|
LITERAL 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: third-highest mountain range in Africa | Statement: [Rwenzori Mountains, rankByElevationInAfrica, third-highest mountain range in Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByElevationInAfrica Context triple: [Rwenzori Mountains, rankByElevationInAfrica, third-highest mountain range in Africa]
-
A.
rankInAfricaByLength
Indicates the position of something in an ordered list of African entities sorted by their length (e.g., size, distance, or extent).
-
B.
rankByHeightWorld
Indicates an ordering of entities based on their relative height compared to all others in the world.
-
C.
areaRankingInAfrica
Indicates the relative position of an entity in a size-based ranking of areas within Africa.
-
D.
summitElevationRank
chosen
Indicates the relative position of a summit in an ordered list based on its elevation compared to other summits.
-
E.
alternativePeakForContinent
Indicates that a given peak is recognized as an alternative highest point for a specified continent, typically due to differing criteria or measurement standards.
- F. None of above.
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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada4e73cc88190846ef37ccf1a0de7 |
completed | March 8, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_69ad9df455088190940ad04419772dc8 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:04 p.m.