Triple
T7045141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramoji Film City |
E163612
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Ramoji Rao |
E646379
|
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: Ramoji Rao | Statement: [Ramoji Film City, namedAfter, Ramoji Rao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramoji Rao Context triple: [Ramoji Film City, namedAfter, Ramoji Rao]
-
A.
Ramoji Rao
chosen
Ramoji Rao is an Indian media baron and entrepreneur best known as the founder of the vast Ramoji Film City studio complex and the Eenadu media group.
-
B.
Allu Venkatesh
Allu Venkatesh is an Indian film producer and member of the prominent Allu family in the Telugu cinema industry.
-
C.
C. V. Mohan
C. V. Mohan is an Indian film producer best known as a co-founder of the prominent Telugu film production company Mythri Movie Makers.
-
D.
Allu Aravind
Allu Aravind is a prominent Indian film producer and distributor, best known for founding the production company Geetha Arts and producing numerous successful Telugu and Hindi films.
-
E.
Venkatesh Daggubati
Venkatesh Daggubati is a prominent Indian film actor best known for his work in Telugu cinema, where he has had a successful career spanning several decades.
- 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e238c7a4819095f5ff7283d48da8 |
completed | March 27, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bf765d2481908d9ba1918f46bcda |
completed | March 28, 2026, 11:45 a.m. |
Created at: March 27, 2026, 2:37 p.m.