Triple
T12771144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanakshahi calendar |
E305248
|
entity |
| Predicate | hasMonth |
P6433
|
FINISHED |
| Object | Sawan |
E874162
|
NE 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: Sawan | Statement: [Nanakshahi calendar, hasMonth, Sawan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sawan Context triple: [Nanakshahi calendar, hasMonth, Sawan]
-
A.
Sawan
chosen
Sawan is a holy month in the Hindu calendar, devoted especially to the worship of Lord Shiva and marked by fasting, pilgrimages, and religious festivals.
-
B.
Ashadha
Ashadha is a month in the traditional Hindu lunar calendar, typically falling around June–July, associated with the onset of the monsoon season in the Indian subcontinent.
-
C.
Bhadrapada
Bhadrapada is a month in the Hindu lunar calendar, typically falling around August–September, associated with major festivals such as Ganesh Chaturthi.
-
D.
Margazhi
Margazhi is a winter month in the Tamil calendar, traditionally associated with religious observances, devotional music, and early-morning temple rituals.
-
E.
Uttar Falguni
Uttar Falguni is a classic Bengali film best known for featuring an acclaimed dual-role performance by legendary actress Suchitra Sen.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df4b36c81909bcc913dd5e535f8 |
completed | April 10, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684f9ba848190b680d730b6a3b972 |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 9, 2026, 5:28 p.m.