Triple
T20671273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kielce University of Technology |
E508028
|
entity |
| Predicate | hasRDFOType |
P140992
|
FINISHED |
| Object | tertiary education institution |
—
|
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: tertiary education institution | Statement: [Kielce University of Technology, hasRDFOType, tertiary education institution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRDFOType Context triple: [Kielce University of Technology, hasRDFOType, tertiary education institution]
-
A.
hasTypeOfResource
Indicates that an entity is associated with a specific category or kind of resource it represents or utilizes.
-
B.
hasAxiomSchema
Indicates that one entity is associated with, defined by, or governed through a particular axiom schema.
-
C.
hasRecordType
Indicates that an entity is associated with or classified under a specific type or category of record.
-
D.
hasRootType
Indicates that an entity possesses or is associated with a primary or fundamental type that serves as its root classification.
-
E.
hasTypeSystem
Indicates that an entity employs, is governed by, or is associated with a particular type system (a defined set of rules for classifying and constraining types).
- F. None of above. chosen
Provenance (4 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c92aa8819096fbe0ca5101d01b |
completed | April 20, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e5c03caee881908be4dd25796a03d5 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3caef50819093c8159fe8d6435b |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 11:44 a.m.