Triple
T2205633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kumbakonam, Madras Presidency, British India |
E50589
|
entity |
| Predicate | MahamahamFrequency |
P35915
|
FINISHED |
| Object | once every 12 years |
—
|
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: once every 12 years | Statement: [Kumbakonam, Madras Presidency, British India, MahamahamFrequency, once every 12 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MahamahamFrequency Context triple: [Kumbakonam, Madras Presidency, British India, MahamahamFrequency, once every 12 years]
-
A.
MahaKumbhFrequency
Indicates how often the Maha Kumbh event occurs in time (i.e., the temporal frequency with which it is held).
-
B.
KumbhMelaFrequency
chosen
Indicates how often the Kumbh Mela event occurs or is held over time.
-
C.
largestInflowRiver
Indicates that one river has the greatest volume of water flowing into a specified body (such as a lake, sea, or another river) compared to all other contributing rivers.
-
D.
numberOfPilgrimagesToMecca
Indicates the count of times an entity has undertaken a pilgrimage to Mecca.
-
E.
hasTidalRange
Indicates the relationship between a location or body of water and the magnitude of difference between its high and low tide levels.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.