Triple
T32846990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgorod State National Research University |
E840124
|
entity |
| Predicate | hasResearchAreasIn |
P934
|
FINISHED |
| Object | applied sciences |
—
|
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: applied sciences | Statement: [Belgorod State National Research University, hasResearchAreasIn, applied sciences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResearchAreasIn Context triple: [Belgorod State National Research University, hasResearchAreasIn, applied sciences]
-
A.
hasResearchArea
chosen
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
B.
isInResearchArea
Indicates that one entity falls within, or is relevant to, the specified research area of another entity.
-
C.
hasStudyAreas
Indicates that an entity includes, encompasses, or is associated with one or more specific areas of study.
-
D.
hasResearchComponent
Indicates that an entity includes, involves, or is associated with a research-related component or activity.
-
E.
usesResearchSubject
Indicates that one entity employs or utilizes another entity as a research subject in a study or investigation.
- 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_69f349412c78819084459850e11d29f7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0317eaf4e88190a6f6419cb4ef7547 |
completed | May 12, 2026, 12:07 p.m. |
| PD | Predicate disambiguation | batch_6a03179da394819095e3d346c3785d74 |
completed | May 12, 2026, 12:05 p.m. |
Created at: May 1, 2026, 1:17 a.m.