Triple
T7124413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamakhya Temple |
E166023
|
entity |
| Predicate | stateProtectedMonument |
P46320
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Kamakhya Temple, stateProtectedMonument, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateProtectedMonument Context triple: [Kamakhya Temple, stateProtectedMonument, Yes]
-
A.
monumentState
Indicates that a monument is located within, or officially associated with, a particular state or state-level administrative region.
-
B.
monumentStatus
chosen
Indicates the official designation or condition of an entity as a monument, such as whether it is recognized, protected, or classified under heritage or preservation status.
-
C.
significantMonument
Indicates that something is a monument of notable historical, cultural, or symbolic importance.
-
D.
builtMonument
Indicates that one entity constructed or created a monument in honor of, or related to, another entity.
-
E.
hasNumberOfMonuments
Indicates the specific count of monuments associated with or present in a given entity.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e64c0f688190a9b7482d86c2f033 |
completed | March 27, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c7289881909f3b533c384f9ed4 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:44 p.m.