Triple
T22229697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yash Chopra |
E549433
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Chopra |
—
|
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: Chopra | Statement: [Yash Chopra, familyName, Chopra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chopra Context triple: [Yash Chopra, familyName, Chopra]
-
A.
Chopra
chosen
Chopra is an Indian surname most prominently associated with actress and global icon Priyanka Chopra Jonas.
-
B.
Gotham Chopra
Gotham Chopra is an American filmmaker, author, and media entrepreneur known for creating and producing documentaries and series that explore sports, spirituality, and popular culture.
-
C.
Chaitanya Chopra
Chaitanya Chopra is a character from the 2019 American comedy film "Bad Words."
-
D.
Zuni Chopra
Zuni Chopra is an Indian author and poet known for her fantasy novel "The House That Spoke" and for being the daughter of filmmaker Vidhu Vinod Chopra.
-
E.
Deepak Chopra
Deepak Chopra is an Indian-American author and alternative medicine advocate known for popularizing New Age spirituality and mind-body wellness concepts worldwide.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf173308190a3d21bfc59b39728 |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:37 p.m.