Triple
T16789852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinkoku Maru |
E408077
|
entity |
| Predicate | hasDivingDepth |
P124639
|
FINISHED |
| Object | approximately 12–40 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: approximately 12–40 meters | Statement: [Shinkoku Maru, hasDivingDepth, approximately 12–40 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDivingDepth Context triple: [Shinkoku Maru, hasDivingDepth, approximately 12–40 meters]
-
A.
hasDiveDifficulty
Indicates that an action or event of diving is associated with a specified level of difficulty.
-
B.
hasDivingComponent
Indicates that an activity, event, or process includes or involves a diving-related element or action.
-
C.
maximumDiveDepth
Indicates the greatest depth below the surface that an entity is capable of or allowed to dive.
-
D.
hasDiveType
Indicates that an entity performs or is associated with a specific type or category of dive.
-
E.
diveSpeed
Indicates the speed at which an entity moves downward or descends, typically through a fluid such as air or water.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a50e18819090a30e1f38e520e0 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326bac94481908c082117553320f8 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:22 a.m.