Triple
T10212870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dil Se.. |
E242373
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Shah Rukh Khan |
E174331
|
NE FINISHED |
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: Shah Rukh Khan | Statement: [Dil Se.., starring, Shah Rukh Khan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shah Rukh Khan Context triple: [Dil Se.., starring, Shah Rukh Khan]
-
A.
Shah Rukh Khan
chosen
Shah Rukh Khan is a hugely influential Indian film actor and producer, often called the "King of Bollywood," known for his prolific career in Hindi cinema and global cultural impact.
-
B.
Salman Khan
Salman Khan is an American educator and entrepreneur best known as the founder of the online learning platform Khan Academy.
-
C.
Aamir Khan
Aamir Khan is a renowned Indian film actor, director, and producer known for his critically acclaimed and socially impactful movies in Bollywood.
-
D.
Saif Ali Khan
Saif Ali Khan is a prominent Indian film actor and producer known for his work in Hindi cinema and for being a member of the Pataudi royal family.
-
E.
Akshaye Khanna
Akshaye Khanna is an Indian film actor known for his versatile performances in Hindi cinema across both commercial hits and critically acclaimed dramas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa23bce881909b5deac612ec22cb |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652e25be88190a6f1763e9e86666a |
completed | April 8, 2026, 1:06 p.m. |
Created at: April 6, 2026, 11:03 a.m.