Triple
T20596428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kailasanathar Temple, Kanchipuram |
E506059
|
entity |
| Predicate | hasVimana |
P140709
|
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: [Kailasanathar Temple, Kanchipuram, hasVimana, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVimana Context triple: [Kailasanathar Temple, Kanchipuram, hasVimana, yes]
-
A.
hasNave
Indicates that one entity (typically a building or structure) possesses or includes a nave as a distinct architectural part.
-
B.
VajranabhaIs
Indicates that something or someone is identified as or characterized by being Vajranabha.
-
C.
hasDevata
Indicates a relationship in which something is associated with, presided over by, or dedicated to a particular deity or divine being.
-
D.
hasVirama
Indicates that a character or script element is associated with a virama sign, typically used to suppress the inherent vowel or join consonants in abugida writing systems.
-
E.
hasNavePlan
Indicates that an entity possesses or is associated with a specific plan or layout for a nave (the central part of a church or similar building).
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1bea1c81908b85f38b2a471285 |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a9f3f88190b961db9aca36f7da |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:40 a.m.