Triple
T5822711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filozofická fakulta Univerzity Karlovy |
E129147
|
entity |
| Predicate | nabízí studijní program |
P24838
|
FINISHED |
| Object | bakalářské studium |
—
|
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: bakalářské studium | Statement: [Filozofická fakulta Univerzity Karlovy, nabízí studijní program, bakalářské studium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nabízí studijní program Context triple: [Filozofická fakulta Univerzity Karlovy, nabízí studijní program, bakalářské studium]
-
A.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
B.
hasUndergraduatePrograms
Indicates that an educational institution offers one or more undergraduate-level academic programs.
-
C.
offersFieldOfStudy
Indicates that an institution or program provides a particular field of study as an available area of academic focus.
-
D.
offersLevelOfStudy
chosen
Indicates that an institution or program provides a particular level or type of study (e.g., undergraduate, graduate, doctoral) as an available option.
-
E.
hasModeOfStudy
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_69c0084869e881908d7859492183ca7b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.