Triple
T4473132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akatsuki |
E98541
|
entity |
| Predicate | UVIPurpose |
P79
|
FINISHED |
| Object | ultraviolet imaging of cloud patterns and SO2 distribution |
—
|
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: ultraviolet imaging of cloud patterns and SO2 distribution | Statement: [Akatsuki, UVIPurpose, ultraviolet imaging of cloud patterns and SO2 distribution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: UVIPurpose Context triple: [Akatsuki, UVIPurpose, ultraviolet imaging of cloud patterns and SO2 distribution]
-
A.
accessPurpose
Indicates that one entity uses or accesses another entity specifically for a defined purpose or intended use.
-
B.
purpose
chosen
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another entity.
-
C.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
D.
reasonForUse
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
E.
primaryUseInFeed
Indicates that something is the main or most common way an item is used or presented within a feed.
- 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_69b3454b4ae481908967426dd37284d6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356fb69a0819099f0005779f4fcac |
completed | March 13, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69b3563bf4f8819081726cde3a34460b |
completed | March 13, 2026, 12:11 a.m. |
Created at: March 12, 2026, 11:35 p.m.