Triple
T2861390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sigsbee Deep |
E63329
|
entity |
| Predicate | hasWaterDepthCategory |
P42757
|
FINISHED |
| Object | abyssal zone |
—
|
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 zone | Statement: [Sigsbee Deep, hasWaterDepthCategory, abyssal zone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterDepthCategory Context triple: [Sigsbee Deep, hasWaterDepthCategory, abyssal zone]
-
A.
riverbedDepth
Indicates the depth or vertical distance from the water surface to the bottom of a river at a given location or time.
-
B.
hasBerthDepth
Indicates the depth of water available at a specific berth where a vessel can be moored.
-
C.
seaDepth
Indicates the measured vertical distance from the sea surface down to the seafloor at a given location.
-
D.
seaDepthRange
Indicates the minimum and maximum water depth values associated with a given sea or marine location.
-
E.
hasWaterActivity
Indicates that one entity possesses, exhibits, or is characterized by a particular level or type of water-related activity (such as moisture content, water availability, or water-based processes).
- 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf8df8288190816767169ea7cbf9 |
completed | March 7, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69abdd123ec48190af50a1859aea50b7 |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abddedd72c819094a9c4161af07780 |
completed | March 7, 2026, 8:12 a.m. |
Created at: March 6, 2026, 10:02 p.m.