Triple
T7165693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jambukeswarar Temple, Thiruvanaikaval |
E167061
|
entity |
| Predicate | hasNumberOfPrakaras |
P75233
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Jambukeswarar Temple, Thiruvanaikaval, hasNumberOfPrakaras, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfPrakaras Context triple: [Jambukeswarar Temple, Thiruvanaikaval, hasNumberOfPrakaras, 5]
-
A.
hasNumberOfDivyaDesams
Indicates the specific count of Divya Desams 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.
isPancharangaKshetram
Indicates that a temple or sacred site is recognized as one of the Pancharanga Kshetrams, the five traditional holy shrines dedicated to Lord Ranganatha (Vishnu) along the Kaveri river.
-
D.
hasGhatCount
Indicates the number of ghats associated with a given entity.
-
E.
hasNumberOfWuku
Indicates the relationship that specifies how many wuku (traditional Javanese calendar weeks) are associated with a given entity.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e832d2548190aacff0de80dbc268 |
completed | March 27, 2026, 8:27 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:47 p.m.