Triple
T5822684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filozofická fakulta Univerzity Karlovy |
E129147
|
entity |
| Predicate | jazyk výuky |
P56
|
FINISHED |
| Object | čeština |
—
|
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: čeština | Statement: [Filozofická fakulta Univerzity Karlovy, jazyk výuky, čeština]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jazyk výuky Context triple: [Filozofická fakulta Univerzity Karlovy, jazyk výuky, čeština]
-
A.
languageOfTeachings
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
-
B.
primaryLanguageOfInstruction
chosen
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
C.
alsoUsesLanguageOfInstruction
Indicates that an entity, in addition to its primary language, uses the same language that is designated as the language of instruction in a given context.
-
D.
languageOfAwardingInstitution
Indicates the language in which the awarding institution formally grants or documents the award.
-
E.
taughtAsForeignLanguageIn
Indicates that a language is taught as a foreign (non-native) language within a particular educational context or institution.
- 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.