Triple
T105747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East China Sea |
E2132
|
entity |
| Predicate | maxDepth |
P968
|
FINISHED |
| Object | over 2,000 meters |
—
|
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: over 2,000 meters | Statement: [East China Sea, maxDepth, over 2,000 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxDepth Context triple: [East China Sea, maxDepth, over 2,000 meters]
-
A.
maximumDepth
chosen
Indicates the greatest extent or deepest level reached by something within a given context or structure.
-
B.
hasMaximumDepth
Indicates that an entity possesses a greatest or limiting depth value beyond which it does not extend.
-
C.
hasAverageDepth
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
-
D.
depth
Indicates the vertical distance from a reference surface or top point down to a lower point or bottom within a medium or space.
-
E.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a256ec650c8190bee2067e37065527 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563d33788190999d471b486d5603 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.