Triple
T19099251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shunga dynasty |
E467485
|
entity |
| Predicate | associatedWithReligionDebate |
P53157
|
FINISHED |
| Object | Brahmanism and Buddhism |
—
|
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: Brahmanism and Buddhism | Statement: [Shunga dynasty, associatedWithReligionDebate, Brahmanism and Buddhism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithReligionDebate Context triple: [Shunga dynasty, associatedWithReligionDebate, Brahmanism and Buddhism]
-
A.
associatedReligionOrBelief
Indicates that an entity is connected to, identified with, or characterized by a particular religion or belief system.
-
B.
religiousControversy
chosen
Indicates a relationship in which entities are involved in a dispute, conflict, or debate specifically concerning religious beliefs, practices, or institutions.
-
C.
religiousTopicAddressed
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
-
D.
subjectReligion
Indicates that the subject is associated with, practices, or adheres to a particular religion.
-
E.
religiousAttitude
Indicates an entity’s stance, disposition, or orientation toward religion or religious beliefs.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36c55688190b4a5135ea10c9924 |
completed | April 20, 2026, 8:27 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:04 p.m.