Triple
T21944376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haasil |
E541897
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Aseem Sinha |
—
|
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 Sinha | Statement: [Haasil, editedBy, Aseem Sinha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aseem Sinha Context triple: [Haasil, editedBy, Aseem Sinha]
-
A.
Aseem Sinha
chosen
Aseem Sinha is a film editor known for his work on the acclaimed Hindi film "Suraj Ka Satvan Ghoda."
-
B.
Aseem Mishra
Aseem Mishra is an Indian cinematographer known for his work on acclaimed Hindi films, including collaborations with director Tigmanshu Dhulia and others.
-
C.
Aseem Shukla
Aseem Shukla is an Indian American urologic surgeon and public advocate known for co-founding and promoting the Hindu American Foundation.
-
D.
Aseem Kishore
Aseem Kishore is a technology writer and blogger known for creating practical guides and tutorials on software, web development, and digital tools.
-
E.
Sampath Chawla
Sampath Chawla is the eccentric young man who becomes a reluctant holy figure after retreating to a guava tree in Kiran Desai’s novel "Hullabaloo in the Guava Orchard."
- 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.