Triple
T20898767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles University Faculty of Law |
E514612
|
entity |
| Predicate | offersProgramInLanguage |
P29959
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Charles University Faculty of Law, offersProgramInLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersProgramInLanguage Context triple: [Charles University Faculty of Law, offersProgramInLanguage, English]
-
A.
offersProgramsInLanguage
chosen
Indicates that an entity provides or conducts its programs using a specified language.
-
B.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
C.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
-
D.
offersProgramComponent
Indicates that an entity provides or makes available a specific program component as part of its offerings.
-
E.
offersProgramsFor
Indicates that one entity provides or makes available specific programs or courses intended for another entity.
- 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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8f92bd88190b59b2131ad1d9aa1 |
completed | April 21, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:47 p.m.