Triple
T31115433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hochschule Fresenius Idstein campus |
E793071
|
entity |
| Predicate | hasLearningFormat |
P40336
|
FINISHED |
| Object | full-time study |
—
|
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: full-time study | Statement: [Hochschule Fresenius Idstein campus, hasLearningFormat, full-time study]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLearningFormat Context triple: [Hochschule Fresenius Idstein campus, hasLearningFormat, full-time study]
-
A.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
B.
hasTrainingMedium
Indicates that an entity uses or is associated with a particular medium, format, or environment for training.
-
C.
trainingFormat
Indicates the specific method or medium through which training is delivered or conducted.
-
D.
isTaughtFormally
Indicates that one entity provides structured, formal instruction or education to another entity.
-
E.
hasModeOfStudy
chosen
Indicates the method or format by which an entity (typically a learner) undertakes their studies, such as full-time, part-time, online, or in-person.
- 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_69f224d0a7688190af3fe3e6e26d01ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd09840ea88190a2e6d7e577ade717 |
completed | May 7, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69fd064c49988190afadddbd04d7cb94 |
completed | May 7, 2026, 9:38 p.m. |
Created at: April 29, 2026, 9:04 p.m.