Triple
T8960853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Феодосій Григорович Добжанський |
E213998
|
entity |
| Predicate | науковаСпеціалізація |
P778
|
FINISHED |
| Object | генетика популяцій |
—
|
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: генетика популяцій | Statement: [Феодосій Григорович Добжанський, науковаСпеціалізація, генетика популяцій]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: науковаСпеціалізація Context triple: [Феодосій Григорович Добжанський, науковаСпеціалізація, генетика популяцій]
-
A.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
B.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
C.
secondaryDiscipline
Indicates that an entity has an additional, subordinate field of study or area of specialization associated with it, distinct from its primary discipline.
-
D.
specializationRegion
Indicates that something is specialized, adapted, or specifically applicable to a particular geographic or spatial region.
-
E.
academicFocus
chosen
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
- 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_69ca839cd6008190a1546a701a56710c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6748baa88190ac54e701dc4d6212 |
completed | April 1, 2026, 12:31 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed74d288190b712d739805579dc |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7 p.m.