Triple
T13362892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Point Lenana |
E318862
|
entity |
| Predicate | rankingOnMountKenyaByHeight |
P109627
|
FINISHED |
| Object | third-highest peak |
—
|
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 peak | Statement: [Point Lenana, rankingOnMountKenyaByHeight, third-highest peak]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingOnMountKenyaByHeight Context triple: [Point Lenana, rankingOnMountKenyaByHeight, third-highest peak]
-
A.
countryRankByHeight
Indicates the relative position of a country when countries are ordered by the height of something (e.g., average elevation, tallest point, or average citizen height).
-
B.
regionRankByHeight
Indicates the relative ordering of regions based on their height or elevation.
-
C.
rankingByHeightInAfrica
Indicates that entities are ordered or compared based on their height specifically within the context of Africa.
-
D.
countryRankByHeightAtCompletion
Indicates the position of a country in an ordered list based on the height of something (typically a structure or project) at the time it was completed.
-
E.
rankByHeightWorld
Indicates an ordering of entities based on their relative height compared to all others in the world.
- F. None of above. chosen
Provenance (4 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da628affd081909f1790d333f0eef4 |
completed | April 11, 2026, 3:02 p.m. |
| PD | Predicate disambiguation | batch_69d9a02c9abc8190b328e7bae747bfc5 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:32 p.m.