Triple
T28937985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanaka Durga |
E730368
|
entity |
| Predicate | sharesTempleWith |
P74349
|
FINISHED |
| Object | Malleswara Swamy |
—
|
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: Malleswara Swamy | Statement: [Kanaka Durga, sharesTempleWith, Malleswara Swamy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesTempleWith Context triple: [Kanaka Durga, sharesTempleWith, Malleswara Swamy]
-
A.
templeSharedWith
chosen
Indicates that a temple is used, occupied, or regarded as belonging to more than one party, group, or entity.
-
B.
sharesTempleChurchWith
Indicates that two entities use or are associated with the same building or site that functions as both a temple and a church.
-
C.
associatedTemple
Indicates a relationship where one entity is linked or connected to a particular temple, typically as its relevant or related religious site.
-
D.
templeUse
Indicates that something is used as, functions as, or serves the purpose of a temple.
-
E.
associatedWithTempleTown
Indicates a relationship where an entity has a connection or linkage to a town that is characterized by or centered around a temple.
- 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_69f043ea0aa88190a25acbf46157995a |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: April 28, 2026, 8:34 a.m.