Triple
T27141181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knut and Alice Wallenberg Foundation |
E681818
|
entity |
| Predicate | grantScope |
P113843
|
FINISHED |
| Object | primarily Swedish researchers |
—
|
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: primarily Swedish researchers | Statement: [Knut and Alice Wallenberg Foundation, grantScope, primarily Swedish researchers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grantScope Context triple: [Knut and Alice Wallenberg Foundation, grantScope, primarily Swedish researchers]
-
A.
grantLocation
Indicates that an entity is located at, based in, or associated with a particular place or geographic location.
-
B.
grantUse
Indicates that one entity gives another entity permission or authorization to use something.
-
C.
issuerScope
chosen
Indicates the range or domain of authority, responsibility, or applicability associated with the entity acting as the issuer in a given context.
-
D.
grantType
Indicates the specific authorization or credential flow used to obtain access or permissions in a grant-based process.
-
E.
accessScope
Indicates the extent or boundaries of access that one entity has to another entity or resource.
- 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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 27, 2026, 9:09 a.m.