Triple
T244199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Physical Education and Sport, Charles University |
E4999
|
entity |
| Predicate | trainsProfession |
P788
|
FINISHED |
| Object | physical education teachers |
—
|
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: physical education teachers | Statement: [Faculty of Physical Education and Sport, Charles University, trainsProfession, physical education teachers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainsProfession Context triple: [Faculty of Physical Education and Sport, Charles University, trainsProfession, physical education teachers]
-
A.
trains
chosen
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
notableTrain
Indicates that there is a train or rail service associated with the subject that is considered notable or significant in some way.
-
C.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
D.
transports
Indicates that one entity carries or conveys another entity from one place to another.
-
E.
transportationRole
Indicates a role or function that an entity has specifically in the context of providing, operating, or supporting transportation.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.