Triple
T18451011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satya Yuga |
E450780
|
entity |
| Predicate | durationInHumanYears |
P49590
|
FINISHED |
| Object | 1,728,000 human years |
—
|
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: 1,728,000 human years | Statement: [Satya Yuga, durationInHumanYears, 1,728,000 human years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: durationInHumanYears Context triple: [Satya Yuga, durationInHumanYears, 1,728,000 human years]
-
A.
countsYearsFrom
Indicates a temporal relationship where the number of years is measured starting from a specified reference point or event.
-
B.
durationInYears
Indicates the length of time associated with something, measured in whole or fractional years.
-
C.
eraLengthYears
chosen
Indicates the duration of an era measured in years.
-
D.
approximateTimeInYear
Indicates that one time-related entity represents an estimated or non-exact point or interval within a given year for another entity.
-
E.
approximateAgeBeforePresent
Indicates that one entity’s age is an estimated value measured as a time interval before the present moment.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52648476c8190a5d8c3297d836f62 |
completed | April 19, 2026, 7 p.m. |
| PD | Predicate disambiguation | batch_69e469d05cf4819099baf1665a9cf18a |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:31 a.m.