Triple
T1418715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bihu |
E31973
|
entity |
| Predicate | religiousNature |
P27555
|
FINISHED |
| Object | primarily secular |
—
|
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: primarily secular | Statement: [Bihu, religiousNature, primarily secular]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousNature Context triple: [Bihu, religiousNature, primarily secular]
-
A.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
B.
religiousMood
Indicates a prevailing emotional or spiritual atmosphere associated with religious experience, practice, or devotion between entities.
-
C.
otherReligion
Indicates that one entity follows or is associated with a religion that is different from the religion of another entity.
-
D.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
E.
laterReligion
Indicates that one religion or religious affiliation chronologically follows or replaces another for the same entity.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c40631e881909ddf81a2eb84af1c |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:59 p.m.