Triple
T114641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Letters |
E2316
|
entity |
| Predicate | hasApproximateStartTime |
P877
|
FINISHED |
| Object | 15th century |
—
|
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: 15th century | Statement: [Republic of Letters, hasApproximateStartTime, 15th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateStartTime Context triple: [Republic of Letters, hasApproximateStartTime, 15th century]
-
A.
startDate
Indicates the point in time when an event, state, or relationship begins.
-
B.
dateApproximate
chosen
Indicates that the associated date is not exact but estimated or approximate rather than precisely known.
-
C.
inUseSince
Indicates that an entity has been actively in use starting from a specified point in time.
-
D.
commitmentTiming
Indicates the point in time or period relative to an event or agreement when a commitment is made, becomes effective, or is expected to be fulfilled.
-
E.
hasLongTermDatasetSince
Indicates that an entity has maintained or used a particular dataset continuously starting from a specified point in 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564417848190a8a8a38e97348963 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.