Triple
T10401825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rang De Basanti |
E245166
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Soha Ali Khan |
E694849
|
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: Soha Ali Khan | Statement: [Rang De Basanti, castMember, Soha Ali Khan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soha Ali Khan Context triple: [Rang De Basanti, castMember, Soha Ali Khan]
-
A.
Soha Ali Khan
chosen
Soha Ali Khan is an Indian film actress known for her work in Hindi and Bengali cinema and as a member of the prominent Pataudi–Tagore family.
-
B.
Suhana Khan
Suhana Khan is an Indian actress and media personality, widely recognized as the daughter of Bollywood superstar Shah Rukh Khan and for her emerging career in Hindi cinema.
-
C.
Lara Dutta
Lara Dutta is an Indian actress, model, and former Miss Universe (2000) known for her work in Bollywood films.
-
D.
Kiara Advani
Kiara Advani is an Indian film actress known for her work in Hindi and Telugu cinema, with notable roles in films like "Kabir Singh," "Shershaah," and "MS Dhoni: The Untold Story."
-
E.
Kajal Aggarwal
Kajal Aggarwal is a popular Indian actress best known for her leading roles in Telugu and Tamil cinema, as well as appearances in Hindi films.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e42da08190a5383df3df6d3c18 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90d8580788190a4948984fbc2f57d |
completed | April 10, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:08 p.m.