Triple
T29306583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foundation's Edge |
E743110
|
entity |
| Predicate | timeSettingRelativeToSeries |
P40399
|
FINISHED |
| Object | centuries after the founding of the Foundation |
—
|
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: centuries after the founding of the Foundation | Statement: [Foundation's Edge, timeSettingRelativeToSeries, centuries after the founding of the Foundation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSettingRelativeToSeries Context triple: [Foundation's Edge, timeSettingRelativeToSeries, centuries after the founding of the Foundation]
-
A.
timeInSeries
Indicates that one temporal value occurs within the duration or sequence span defined by another in a series.
-
B.
timePeriodInSeries
Indicates the specific time span or interval during which an installment, episode, or part occurs within a larger series or sequence.
-
C.
timeframeRelative
chosen
Indicates a temporal relationship where one event, state, or condition is positioned in time relative to another (e.g., before, after, or overlapping).
-
D.
timeSettingVariant
Indicates a relationship where one time setting is an alternative or modified version of another time setting.
-
E.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
- 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_69f09123ed9881909f351f7541933f5e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f66d7765208190b87b1cc6d96a151c |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 1:14 p.m.