Triple
T16527632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rajkummar Rao |
E401481
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Rajkummar Rao |
E401481
|
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: Rajkummar Rao | Statement: [Rajkummar Rao, name, Rajkummar Rao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rajkummar Rao Context triple: [Rajkummar Rao, name, Rajkummar Rao]
-
A.
Rajkummar Rao
chosen
Rajkummar Rao is an acclaimed Indian film actor known for his versatile performances in Hindi cinema, particularly in critically praised independent and mainstream films.
-
B.
Varun Dhawan
Varun Dhawan is a popular Indian film actor known for his work in contemporary Bollywood cinema, particularly in commercial comedies and dramas.
-
C.
Ravi Kishan
Ravi Kishan is an Indian actor, film producer, and politician best known for his work in Bhojpuri cinema as well as Hindi and Telugu films.
-
D.
Aditya Sood
Aditya Sood is a film producer known for his work on high-profile Hollywood projects, including the thriller-comedy "Cocaine Bear."
-
E.
Shahid Kapoor
Shahid Kapoor is a popular Indian film actor known for his versatile performances in Hindi cinema, including acclaimed roles in films like "Jab We Met," "Haider," and "Kabir Singh."
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed4b8a08190b5f179fc583001a6 |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d29ee288190b59160db43069358 |
completed | May 10, 2026, 2:58 p.m. |
Created at: April 10, 2026, 5:14 a.m.