Triple
T32017853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Natural Science Foundation of China |
E817593
|
entity |
| Predicate | hasGrantType |
P10368
|
FINISHED |
| Object | general program |
—
|
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: general program | Statement: [National Natural Science Foundation of China, hasGrantType, general program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrantType Context triple: [National Natural Science Foundation of China, hasGrantType, general program]
-
A.
granteeType
Indicates the classification or category of the entity that receives a grant or is granted a right, benefit, or permission.
-
B.
hasClaimType
Indicates that an entity is associated with or categorized under a specific type of claim.
-
C.
typeOfGrant
chosen
Indicates the specific category or kind of grant associated with an entity.
-
D.
grantType
Indicates the specific authorization or credential flow used to obtain access or permissions in a grant-based process.
-
E.
hasGrantmakingType
Indicates the specific category or mode of grantmaking associated with an entity, such as how it provides or administers grants.
- 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_69f348f9e5d081908cc3f57c4942af52 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: May 1, 2026, 12:16 a.m.