Triple
T25283205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arupadai Veedu temples |
E633870
|
entity |
| Predicate | numberOfConstituentTemples |
P43478
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Arupadai Veedu temples, numberOfConstituentTemples, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfConstituentTemples Context triple: [Arupadai Veedu temples, numberOfConstituentTemples, 6]
-
A.
hasTempleCount
chosen
Indicates that an entity is associated with a specified number of temples.
-
B.
pilgrimageTempleCount
Indicates the number of temples associated with or visited during a particular pilgrimage.
-
C.
numberOfAltars
Indicates the quantity of altars associated with a given entity or context.
-
D.
isNumberedTempleOf
Indicates that one entity is a specific, designated temple identified by a particular number within a series or system associated with another entity.
-
E.
hasSubTemple
Indicates that one temple includes or contains another temple as a subordinate or component temple within its structure or organization.
- 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_69e75a9402fc81909362ca85277c06d9 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 21, 2026, 1:19 p.m.