Triple
T21163345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirkazhi Brahmapureeswarar Temple |
E521494
|
entity |
| Predicate | numberOfPrakaras |
P75233
|
FINISHED |
| Object | three |
—
|
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: three | Statement: [Sirkazhi Brahmapureeswarar Temple, numberOfPrakaras, three]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPrakaras Context triple: [Sirkazhi Brahmapureeswarar Temple, numberOfPrakaras, three]
-
A.
hasNumberOfPrakaras
chosen
Indicates the relationship specifying how many prakaras (enclosure layers or surrounding structures) are associated with a given entity.
-
B.
numberOfPadarthas
Indicates the relationship that specifies how many distinct padarthas (categories or entities) are associated with or contained in a given subject.
-
C.
numberOfPRBlocks
Indicates the quantity of pull request blocks associated with or contained within a given entity or context.
-
D.
numberOfOpenworkStupas
Indicates the count of openwork stupas associated with or present at a given subject.
-
E.
hasNumberOfKandas
Indicates the relationship specifying how many kandas (sections or books) are associated with 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_69e0b50d1ea481909c07e63c3ead9316 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72533fe88819082e14d71c36140be |
completed | April 21, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69e5f5f8a5bc819081918c7fa8e4496d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:59 p.m.