Triple
T30584172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kakusandha Buddha |
E778459
|
entity |
| Predicate | timeRelativeToGautama |
P169877
|
FINISHED |
| Object | lived long before Gautama Buddha |
—
|
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: lived long before Gautama Buddha | Statement: [Kakusandha Buddha, timeRelativeToGautama, lived long before Gautama Buddha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeRelativeToGautama Context triple: [Kakusandha Buddha, timeRelativeToGautama, lived long before Gautama Buddha]
-
A.
timeRelativeToBirth
Indicates the temporal position of an event or state relative to an entity’s birth (e.g., before, at, or after birth).
-
B.
relativeLengthInYugaCycle
Indicates the proportion of the total Yuga cycle duration that is occupied by a given Yuga or time segment.
-
C.
relativeTimeToGalungan
Indicates the temporal relationship of an event or date with respect to the Balinese holiday Galungan (e.g., how long before or after Galungan it occurs).
-
D.
timeWithMuhammad
Indicates that one entity spends or has spent time together with Muhammad.
-
E.
timeRelationToSaros
Indicates the temporal relationship an event or object has with respect to a specific Saros cycle, such as occurring before, during, or after that cycle.
- 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.