Triple
T30584192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kakusandha Buddha |
E778459
|
entity |
| Predicate | renunciationVehicle |
P169878
|
FINISHED |
| Object | chariot |
—
|
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: chariot | Statement: [Kakusandha Buddha, renunciationVehicle, chariot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: renunciationVehicle Context triple: [Kakusandha Buddha, renunciationVehicle, chariot]
-
A.
usedUnmarkedVehicles
Indicates that the action or operation was carried out using vehicles that bore no identifying marks, logos, or official insignia.
-
B.
usedAsVehicleFor
Indicates that one entity functions as a means of transportation or conveyance for another entity.
-
C.
renunciationContext
Indicates the situational or circumstantial context within which a renunciation (giving up a right, claim, role, or possession) takes place.
-
D.
renouncedBy
Indicates that an entity has been formally rejected, disowned, or given up by another entity.
-
E.
hasVehicularUse
Indicates that something is used for, intended for, or associated with operation by vehicles or vehicular traffic.
- F. None of above. chosen
Provenance (4 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68945093481909c6eba86bc50870e |
completed | May 2, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f6827a7b9c8190ab13605aacc81df9 |
completed | May 2, 2026, 11:02 p.m. |
Created at: April 29, 2026, 8:23 p.m.