Triple
T7911841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annamalaiyar Temple |
E183717
|
entity |
| Predicate | numberOfGopurams |
P79736
|
FINISHED |
| Object | four main gopurams |
—
|
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: four main gopurams | Statement: [Annamalaiyar Temple, numberOfGopurams, four main gopurams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGopurams Context triple: [Annamalaiyar Temple, numberOfGopurams, four main gopurams]
-
A.
hasPilgrimageGhatsIn
Indicates that a place possesses or contains pilgrimage ghats located within the specified area or region.
-
B.
rajagopuramHeight
Indicates the height measurement associated with a rajagopuram (temple gateway tower).
-
C.
numberOfHinduCaves
Indicates the quantity of caves that are identified or classified as Hindu caves in relation to a given subject.
-
D.
hasNumberOfDivyaDesams
Indicates the specific count of Divya Desams associated with a given entity.
-
E.
pilgrimageTempleCount
Indicates the number of temples associated with or visited during a particular pilgrimage.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a725b8c8190a530adb3107a95dd |
completed | March 31, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69cae92f9498819085277879e59aa072 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7882b048190baa333af9f698590 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:04 p.m.