Triple
T21944530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunday |
E541901
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Aseem Mishra |
—
|
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: Aseem Mishra | Statement: [Gunday, cinematographyBy, Aseem Mishra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aseem Mishra Context triple: [Gunday, cinematographyBy, Aseem Mishra]
-
A.
Aseem Mishra
chosen
Aseem Mishra is an Indian cinematographer known for his work on acclaimed Hindi films, including collaborations with director Tigmanshu Dhulia and others.
-
B.
Aseem Shukla
Aseem Shukla is an Indian American urologic surgeon and public advocate known for co-founding and promoting the Hindu American Foundation.
-
C.
Aseem Kishore
Aseem Kishore is a technology writer and blogger known for creating practical guides and tutorials on software, web development, and digital tools.
-
D.
Aseem Sinha
Aseem Sinha is a film editor known for his work on the acclaimed Hindi film "Suraj Ka Satvan Ghoda."
-
E.
Vinay Mishra
Vinay Mishra is an Indian politician serving as a Member of the Legislative Assembly (MLA) from the Dwarka constituency in Delhi.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.