Triple
T22555950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamchatka Trench |
E557681
|
entity |
| Predicate | waterDepthClass |
P42757
|
FINISHED |
| Object | abyssal to hadal depths |
—
|
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: abyssal to hadal depths | Statement: [Kamchatka Trench, waterDepthClass, abyssal to hadal depths]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterDepthClass Context triple: [Kamchatka Trench, waterDepthClass, abyssal to hadal depths]
-
A.
hasWaterDepthCategory
chosen
Indicates the classification of something based on the range or category of its water depth.
-
B.
riverbedDepth
Indicates the depth or vertical distance from the water surface to the bottom of a river at a given location or time.
-
C.
seaDepth
Indicates the measured vertical distance from the sea surface down to the seafloor at a given location.
-
D.
depthBelowSurfaceInMeters
Indicates the vertical distance, measured in meters, that something is located below a reference surface level.
-
E.
depthInMetersWaterEquivalent
Indicates the depth of something expressed as the equivalent thickness of water (in meters) that would produce the same shielding or overburden effect.
- 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f7a4a3c81908fc87f48b6dcbbf7 |
completed | April 29, 2026, 1:31 a.m. |
| PD | Predicate disambiguation | batch_69e898cb3fb48190add6ab24a2df5822 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:52 p.m.