Triple
T21945162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Border |
E541914
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Sunny Deol |
—
|
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: Sunny Deol | Statement: [Border, castMember, Sunny Deol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sunny Deol Context triple: [Border, castMember, Sunny Deol]
-
A.
Sunny Deol
chosen
Sunny Deol is an Indian film actor, director, and politician best known for his powerful action roles and intense performances in Hindi cinema.
-
B.
Bo Derek
Bo Derek is an American actress and model best known for her breakout role in the 1979 film "10," which made her a major sex symbol of the late 20th century.
-
C.
Jackie Shroff
Jackie Shroff is a veteran Indian film actor known for his versatile performances across Hindi cinema since the 1980s.
-
D.
Bobby Deol
Bobby Deol is an Indian film actor known for his work in Hindi cinema, particularly in action and thriller films since the mid-1990s.
-
E.
Ajay Devgn
Ajay Devgn is a prominent Indian film actor, director, and producer known for his intense performances in Hindi cinema and his versatility across action, drama, and comedy roles.
- 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.