Triple
T8549459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malaipadukadām |
E202408
|
entity |
| Predicate | religiousReferences |
P2154
|
FINISHED |
| Object | Murugan worship |
—
|
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: Murugan worship | Statement: [Malaipadukadām, religiousReferences, Murugan worship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousReferences Context triple: [Malaipadukadām, religiousReferences, Murugan worship]
-
A.
religiousTopicAddressed
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
-
B.
religiousElement
chosen
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
C.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
D.
religiousTextOf
Indicates that one entity is a religious text that is sacred to, foundational for, or primarily associated with another entity (such as a religion, denomination, or faith community).
-
E.
subjectReligion
Indicates that the subject is associated with, practices, or adheres to a particular religion.
- 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe753d3608190b0573477182cf194 |
completed | March 31, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69cbd113e05c81908f4f3fc1b5925164 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:19 p.m.