Triple
T6936545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reason over force |
E160566
|
entity |
| Predicate | renderingOf |
P37806
|
FINISHED |
| Object | Jagiellonian University Latin motto |
—
|
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: Jagiellonian University Latin motto | Statement: [Reason over force, renderingOf, Jagiellonian University Latin motto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: renderingOf Context triple: [Reason over force, renderingOf, Jagiellonian University Latin motto]
-
A.
renders
chosen
Indicates that one entity produces, generates, or visually presents another entity, often by transforming data or instructions into a final displayed or usable form.
-
B.
renderedBy
Indicates that something is produced, drawn, or visually generated by a particular agent, tool, or process.
-
C.
renderedUnder
Indicates that one entity was produced, displayed, or executed within the authority, context, or environment provided by another entity.
-
D.
notableRendering
Indicates that one entity is a significant or well-known visual or artistic depiction of another entity.
-
E.
renderingArchitecture
Indicates the specific rendering system or framework used to generate visual output for a given entity or environment.
- 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_69c6884e15208190b9e91487eaafcf85 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e0c74fe48190aeaa018631e52ef6 |
completed | March 27, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bd5a388190a57a96d925696ff6 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:27 p.m.