Triple
T19717654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 日本国际奖 |
E473520
|
entity |
| Predicate | 奖励性质 |
P137057
|
FINISHED |
| Object | 国际性权威大奖 |
—
|
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: 国际性权威大奖 | Statement: [日本国际奖, 奖励性质, 国际性权威大奖]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 奖励性质 Context triple: [日本国际奖, 奖励性质, 国际性权威大奖]
-
A.
rewardUse
Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
-
B.
awardCurrency
Indicates that one entity grants or gives a specified amount of currency to another entity.
-
C.
rewardSignal
Indicates that one entity provides a signal representing feedback or incentive (such as a reward or penalty) to guide another entity’s behavior or learning process.
-
D.
grantedAsRewardFor
Indicates that something is given to an entity specifically as a reward for a particular action, achievement, or service.
-
E.
awardEffect
Indicates that one entity confers or grants a benefit, recognition, or reward that has a particular impact or consequence on another entity.
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6440ec9e881909b75c0ebefab827f |
completed | April 20, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:46 p.m.