Triple
T19429073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pushpaka Vimana |
E486061
|
entity |
| Predicate | timePeriodOfText |
P302
|
FINISHED |
| Object | ancient India |
—
|
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: ancient India | Statement: [Pushpaka Vimana, timePeriodOfText, ancient India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfText Context triple: [Pushpaka Vimana, timePeriodOfText, ancient India]
-
A.
timePeriod
chosen
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
B.
timePeriodFormulated
Indicates the time period during which something (such as a concept, theory, or plan) was formulated or developed.
-
C.
timePeriodImplied
Indicates that a time period is inferred or implied by context rather than being explicitly specified.
-
D.
timeRequiredToRead
Indicates the amount of time needed for an entity (such as a person) to read a given item or content.
-
E.
timePeriodAnalyzed
Indicates that a specified time period is the focus or scope of an analysis or evaluation.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6321b78d08190b86cef7c60cbb61c |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.