Triple
T14169091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Non Incautus Futuri |
E351156
|
entity |
| Predicate | literalMeaningComponent |
P16024
|
FINISHED |
| Object | Non = not |
—
|
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: Non = not | Statement: [Non Incautus Futuri, literalMeaningComponent, Non = not]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literalMeaningComponent Context triple: [Non Incautus Futuri, literalMeaningComponent, Non = not]
-
A.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
-
B.
meaningComponent
chosen
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
C.
literalMeaningApproximation
Indicates that one entity expresses an approximate or rough literal meaning of another entity, rather than an exact or fully precise interpretation.
-
D.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
E.
meaningComponent郎
Indicates that one entity is a semantic component or constituent part of the overall meaning of 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61b472288190b4a271daa54aa6cd |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1 a.m.