Triple
T10171217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afro-Eurasia |
E235333
|
entity |
| Predicate | lowestLandPointMetresBelowSeaLevel |
P211
|
FINISHED |
| Object | 430 |
—
|
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: 430 | Statement: [Afro-Eurasia, lowestLandPointMetresBelowSeaLevel, 430]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowestLandPointMetresBelowSeaLevel Context triple: [Afro-Eurasia, lowestLandPointMetresBelowSeaLevel, 430]
-
A.
partlyBelowSeaLevel
Indicates that an entity’s elevation is such that some, but not all, of it lies below sea level.
-
B.
isBelowSeaLevel
Indicates that one entity’s vertical position is lower than the standard sea level reference point.
-
C.
lowestPoint
chosen
Indicates that one entity is the point with the minimum vertical position or value relative to another entity or within a specified context.
-
D.
maximumDepthBelowSeaLevel
Indicates the greatest vertical distance an entity extends or reaches below sea level.
-
E.
mouthElevationBelowSeaLevel
Indicates that the elevation of the river’s mouth is below sea level.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9e4e0c819097dceb7bf7757948 |
completed | April 2, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.