Triple
T17056257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diamer |
E413827
|
entity |
| Predicate | mountainRankByHeightWorld |
P2472
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Diamer, mountainRankByHeightWorld, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mountainRankByHeightWorld Context triple: [Diamer, mountainRankByHeightWorld, 9]
-
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.
rankByHeightWorld
chosen
Indicates an ordering of entities based on their relative height compared to all others in the world.
-
C.
regionRankByHeight
Indicates the relative ordering of regions based on their height or elevation.
-
D.
continentHighestPointRank
Indicates the relative ranking of a location’s elevation compared to other high points on the same continent, with rank 1 being the highest.
-
E.
countryHighestPointRank
Indicates the relative ranking of a country's highest natural elevation compared to the highest points of other countries.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db7934e881909e9f0ae956fb0816 |
completed | April 18, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.