Triple
T25498404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thiruthani |
E639040
|
entity |
| Predicate | hasReligiousStructureType |
P185183
|
FINISHED |
| Object | hill temple |
—
|
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: hill temple | Statement: [Thiruthani, hasReligiousStructureType, hill temple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousStructureType Context triple: [Thiruthani, hasReligiousStructureType, hill temple]
-
A.
hasReligiousInstitutionType
Indicates that an entity is associated with, or classified by, a specific type of religious institution.
-
B.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
C.
hasReligiousBuildingAlong
Indicates that a religious building is located along the course, path, or extent of the referenced entity.
-
D.
hasClericalStructure
Indicates that an entity possesses an organized clerical or administrative hierarchy or framework.
-
E.
hasReligiousBuildingStyle
Indicates that one entity (typically a building) exhibits or is characterized by the architectural style associated with a particular religion or religious tradition.
- 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_69e75dbbd2a88190b70e1e645de14b9a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bbf812cc8190a16917c5daaff2df |
completed | May 3, 2026, 9:19 p.m. |
Created at: April 21, 2026, 2:41 p.m.