Triple
T926936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laptev Sea |
E20003
|
entity |
| Predicate | hasAverageShelfDepth |
P1176
|
FINISHED |
| Object | less than 50 metres |
—
|
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: less than 50 metres | Statement: [Laptev Sea, hasAverageShelfDepth, less than 50 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAverageShelfDepth Context triple: [Laptev Sea, hasAverageShelfDepth, less than 50 metres]
-
A.
hasAverageDepth
chosen
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
-
B.
depthMetresApprox
Indicates an approximate measurement of how deep something is in metres, rather than an exact value.
-
C.
depthFeetApprox
Indicates an approximate measurement of an entity’s depth expressed in feet.
-
D.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
E.
hasCabinet
Indicates that one entity possesses, includes, or is equipped with a cabinet associated with it.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b388f0bc8190a087222636135ba5 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b2970a4c8190b22cb2fd4706f62b |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.