Triple
T17960742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinbago Knight Riders |
E449073
|
entity |
| Predicate | coOwner |
P347
|
FINISHED |
| Object | Juhi Chawla |
—
|
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: Juhi Chawla | Statement: [Trinbago Knight Riders, coOwner, Juhi Chawla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juhi Chawla Context triple: [Trinbago Knight Riders, coOwner, Juhi Chawla]
-
A.
Juhi Chawla
chosen
Juhi Chawla is a popular Indian actress and film producer known for her work in Hindi cinema since the late 1980s.
-
B.
Bhumika Chawla
Bhumika Chawla is an Indian actress known for her work in Hindi, Telugu, and Tamil films, including notable roles in movies like "Tere Naam" and "Gandhi, My Father."
-
C.
Sanah Kapur
Sanah Kapur is an Indian actress known for her supporting role in the film "Shaandaar" and for being part of the Kapur film family.
-
D.
Vidya Balan
Vidya Balan is an acclaimed Indian actress known for her powerful performances in Hindi cinema and for pioneering strong, female-led films in Bollywood.
-
E.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b131fa8481908cd756f350eb6359 |
completed | April 19, 2026, 10:40 a.m. |
Created at: April 10, 2026, 10:22 a.m.