Triple
T236112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renaissance |
E4826
|
entity |
| Predicate | hasEducationModel |
P784
|
FINISHED |
| Object | studia humanitatis |
—
|
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: studia humanitatis | Statement: [Renaissance, hasEducationModel, studia humanitatis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationModel Context triple: [Renaissance, hasEducationModel, studia humanitatis]
-
A.
educationalModel
chosen
Indicates that one entity serves as an educational model, framework, or paradigm that guides or structures the teaching, learning, or training practices of another entity.
-
B.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
C.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
D.
containsEducationalInstitution
Indicates that one entity geographically or administratively includes or encompasses an educational institution within its boundaries or structure.
-
E.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
- 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_69a25ccab7648190be6e4f5febc1e313 |
completed | Feb. 28, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69a25b5dc640819092669575731c393f |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.