Triple
T17393942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leibniz Institute of Plant Biochemistry |
E422899
|
entity |
| Predicate | hasDoctoralTraining |
P127313
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Leibniz Institute of Plant Biochemistry, hasDoctoralTraining, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDoctoralTraining Context triple: [Leibniz Institute of Plant Biochemistry, hasDoctoralTraining, yes]
-
A.
hasDoctoralSchool
Indicates that an individual or academic entity is affiliated with or obtained their doctoral education from a specific doctoral school or graduate institution.
-
B.
hasDoctoralProgram
Indicates that an institution or academic unit offers and administers a doctoral-level degree program.
-
C.
hasGraduateInstitute
Indicates that an entity is associated with or offers a specific graduate-level educational institution or program.
-
D.
hasDoctoralDegreeFrom
Indicates that an individual holds a doctoral-level academic degree that was awarded by a specified institution.
-
E.
hasAcademicBackgroundIn
Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
- F. None of above. chosen
Provenance (4 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43abbd84881908af91bb7c9784026 |
completed | April 19, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69e3b02ac8688190a7182f1b2151d721 |
completed | April 18, 2026, 4:24 p.m. |
| PDg | Predicate description generation | batch_69e3b2a33e8481908fa6ef45290d08aa |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:45 a.m.