Triple
T37326779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pancharanga Kshetrams |
E926625
|
entity |
| Predicate | hasMemberTemple |
P64892
|
FINISHED |
| Object | Srirangapatna Ranganathaswamy Temple |
—
|
NE NERFINISHED |
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: Srirangapatna Ranganathaswamy Temple | Statement: [Pancharanga Kshetrams, hasMemberTemple, Srirangapatna Ranganathaswamy Temple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberTemple Context triple: [Pancharanga Kshetrams, hasMemberTemple, Srirangapatna Ranganathaswamy Temple]
-
A.
hasTempleOf
chosen
Indicates that a location or entity possesses, contains, or is the site of a temple dedicated to a particular deity, figure, or purpose.
-
B.
hasSubTemple
Indicates that one temple includes or contains another temple as a subordinate or component temple within its structure or organization.
-
C.
hasTempleTree
Indicates that a location or entity possesses or contains a temple-associated tree.
-
D.
hasTempleLocation
Indicates that a temple is located at or associated with a specific place or geographic location.
-
E.
hasTempleCount
Indicates that an entity is associated with a specified number of temples.
- 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_69f76eb386d88190a8d511aa11540dfc |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff891e4b9c8190aa86a339a8944496 |
completed | May 9, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69ff8801180c8190b23e20996ca68e0a |
completed | May 9, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:16 p.m.