Triple
T12506441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctoral Networks |
E298959
|
entity |
| Predicate | fundingCovers |
P25541
|
FINISHED |
| Object | researchers’ living allowance |
—
|
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: researchers’ living allowance | Statement: [Doctoral Networks, fundingCovers, researchers’ living allowance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fundingCovers Context triple: [Doctoral Networks, fundingCovers, researchers’ living allowance]
-
A.
coversCosts
chosen
Indicates that one party assumes responsibility for paying or reimbursing the expenses incurred by another party.
-
B.
mayCover
Indicates that one entity is permitted or able to extend over, include, or provide coverage for another entity, either partially or fully.
-
C.
fundingModel
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
-
D.
fundingContext
Indicates the circumstances, purpose, or conditions under which funding is provided or used in a given relationship or action.
-
E.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfddf38819099263b8b1e804736 |
completed | April 10, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69d94d43b7008190af2648fe09fd6d23 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:57 p.m.