Triple
T17963008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahayuga |
E449130
|
entity |
| Predicate | durationOfDvaparaYugaHumanYears |
P75841
|
FINISHED |
| Object | 864000 |
—
|
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: 864000 | Statement: [Mahayuga, durationOfDvaparaYugaHumanYears, 864000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: durationOfDvaparaYugaHumanYears Context triple: [Mahayuga, durationOfDvaparaYugaHumanYears, 864000]
-
A.
eraLengthYears
Indicates the duration of an era measured in years.
-
B.
durationInYears
chosen
Indicates the length of time associated with something, measured in whole or fractional years.
-
C.
age_billionYears
Indicates the number of billions of years that have elapsed since the referenced entity originated or came into existence.
-
D.
estimatedAgeInMillionsOfYears
Indicates the approximate age of something expressed in units of millions of years.
-
E.
lifetimeInGenerations
Indicates the number of successive generations over which something (e.g., an effect, trait, or validity) persists or remains applicable.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b134bc68819097cc199ea8e80f6c |
completed | April 19, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:22 a.m.