Triple
T20417540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qayamat: City Under Threat |
E500750
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Sharat Saxena |
—
|
NE NERFINISHED |
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: Sharat Saxena | Statement: [Qayamat: City Under Threat, castMember, Sharat Saxena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sharat Saxena Context triple: [Qayamat: City Under Threat, castMember, Sharat Saxena]
-
A.
Sharat Saxena
chosen
Sharat Saxena is an Indian character actor known for his supporting roles in numerous Hindi films and television shows, often portraying tough or authoritative figures.
-
B.
Raghubir Yadav
Raghubir Yadav is an acclaimed Indian actor and singer known for his versatile performances in film, television, and theatre.
-
C.
Raghuveer Chaudhari
Raghuveer Chaudhari is an acclaimed Indian Gujarati writer and scholar renowned for his influential novels, poetry, and literary criticism.
-
D.
Ajit Bhawan
Ajit Bhawan is a historic royal residence in Jodhpur that has been converted into a luxury heritage hotel associated with the Jodhpur royal family.
-
E.
Sudesh Dhankhar
Sudesh Dhankhar is the wife of Indian politician and current Vice President of India, Jagdeep Dhankhar.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a44ecf48190ba5a3872af500dc8 |
completed | April 20, 2026, 7:11 p.m. |
Created at: April 16, 2026, 11:30 a.m.