Triple
T24123224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open University of Cyprus |
E597719
|
entity |
| Predicate | accommodationOf |
P17960
|
FINISHED |
| Object | working adults |
—
|
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: working adults | Statement: [Open University of Cyprus, accommodationOf, working adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accommodationOf Context triple: [Open University of Cyprus, accommodationOf, working adults]
-
A.
sleepingAccommodation
Indicates that one entity serves as a place or facility where another entity can sleep or stay overnight.
-
B.
hasAccommodation
chosen
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
C.
accommodationModel
Indicates the specific type or structure of lodging arrangement that characterizes how an accommodation is organized or provided.
-
D.
passengerAccommodation
Indicates that an entity provides or is designated as seating, lodging, or space intended for use by passengers.
-
E.
accommodationStyle
Indicates the manner or type of lodging or housing arrangement provided or used in a given context.
- 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_69e288c808b881909fed7d18f04bcbbe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dee5937c819092396751c23553ca |
completed | April 29, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:06 p.m.