Triple
T8080911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marudamalai Murugan Temple |
E188611
|
entity |
| Predicate | hasSubShrine |
P27875
|
FINISHED |
| Object | Ganesha shrine |
—
|
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: Ganesha shrine | Statement: [Marudamalai Murugan Temple, hasSubShrine, Ganesha shrine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubShrine Context triple: [Marudamalai Murugan Temple, hasSubShrine, Ganesha shrine]
-
A.
hasSubTemple
Indicates that one temple includes or contains another temple as a subordinate or component temple within its structure or organization.
-
B.
hasShrinesIn
Indicates that one entity possesses or maintains shrines that are located within the area or domain of another entity.
-
C.
hasMajorShrine
Indicates that one entity serves as a principal or primary shrine dedicated to another entity.
-
D.
associatedShrine
chosen
Indicates that there is a specific shrine linked or connected to the given entity, typically as its dedicated or related place of worship or reverence.
-
E.
hasAltar
Indicates that one entity possesses, contains, or includes an altar as part of its features or components.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40a504d48190ace96e814d99b182 |
completed | March 31, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69cb049f1614819087360d1a4c6f0faa |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:28 p.m.