Triple
T7165706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jambukeswarar Temple, Thiruvanaikaval |
E167061
|
entity |
| Predicate | hasTempleTree |
P75235
|
FINISHED |
| Object | Jambu tree |
—
|
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: Jambu tree | Statement: [Jambukeswarar Temple, Thiruvanaikaval, hasTempleTree, Jambu tree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTempleTree Context triple: [Jambukeswarar Temple, Thiruvanaikaval, hasTempleTree, Jambu tree]
-
A.
hasTempleOf
Indicates that a location or entity possesses, contains, or is the site of a temple dedicated to a particular deity, figure, or purpose.
-
B.
hasTempleCount
Indicates that an entity is associated with a specified number of temples.
-
C.
hasSubTemple
Indicates that one temple includes or contains another temple as a subordinate or component temple within its structure or organization.
-
D.
hasTempleCluster
Indicates that an entity possesses or contains a group or complex of temples considered as a single clustered unit.
-
E.
hasHistoricTemple
Indicates that an entity possesses, contains, or is associated with a temple of historical significance.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e832d2548190aacff0de80dbc268 |
completed | March 27, 2026, 8:27 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:47 p.m.