Triple
T10360549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orosius |
E244120
|
entity |
| Predicate | chronologicalScopeOfMainWork |
P82593
|
FINISHED |
| Object | from Creation to his own time |
—
|
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: from Creation to his own time | Statement: [Orosius, chronologicalScopeOfMainWork, from Creation to his own time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chronologicalScopeOfMainWork Context triple: [Orosius, chronologicalScopeOfMainWork, from Creation to his own time]
-
A.
chronologyOf
Indicates that one entity represents the temporal ordering, sequence, or historical timeline of events or states associated with another entity.
-
B.
chronologicallyCovers
Indicates that one time period, event, or sequence extends over and includes the entire chronological span of another.
-
C.
chronologicalRange
chosen
Indicates the temporal span or period over which something occurs, is valid, or is relevant.
-
D.
chronologyType
Indicates the type or system of chronological ordering or dating applied to an event, period, or sequence.
-
E.
chronologicallyFocusesOn
Indicates that something is primarily concerned with or organized around the sequence and progression of events over time.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9609c4481908b7d72ecf1adaa73 |
completed | April 7, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69d4dfa657f481909cc5cc8fec00ad19 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:59 a.m.