Triple
T2877268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kumbhalgarh Fort |
E56906
|
entity |
| Predicate | hasTempleType |
P18959
|
FINISHED |
| Object | Hindu temples |
—
|
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: Hindu temples | Statement: [Kumbhalgarh Fort, hasTempleType, Hindu temples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTempleType Context triple: [Kumbhalgarh Fort, hasTempleType, Hindu temples]
-
A.
templeType
chosen
Indicates the specific category or classification of a temple in terms of its form, function, or religious/architectural style.
-
B.
hasSubTemple
Indicates that one temple includes or contains another temple as a subordinate or component temple within its structure or organization.
-
C.
hasTemplePurpose
Indicates that something (such as a building, site, or structure) is intended, used, or designated for temple-related purposes or functions.
-
D.
hasReligiousInstitutionType
Indicates that an entity is associated with, or classified by, a specific type of religious institution.
-
E.
hasHistoricTemple
Indicates that an entity possesses, contains, or is associated with a temple of historical significance.
- 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abe007329c8190b0bc1851c7307124 |
completed | March 7, 2026, 8:21 a.m. |
| PD | Predicate disambiguation | batch_69abdd142e4c8190b424cb0c5ff40d04 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:03 p.m.