Triple
T2410170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapoor |
E50369
|
entity |
| Predicate | notablePerson |
P304
|
FINISHED |
| Object | Ranbir Kapoor |
E185108
|
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: Ranbir Kapoor | Statement: [Kapoor, notablePerson, Ranbir Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ranbir Kapoor Context triple: [Kapoor, notablePerson, Ranbir Kapoor]
-
A.
Ranbir Kapoor
chosen
Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
-
B.
Ali Fazal
Ali Fazal is an Indian actor known for his work in both Bollywood and international productions, including roles in films like "Victoria & Abdul" and the series "Mirzapur."
-
C.
Kunal Nayyar
Kunal Nayyar is a British-Indian actor best known for playing the socially awkward astrophysicist Rajesh Koothrappali on the hit sitcom "The Big Bang Theory."
-
D.
Sacha Dhawan
Sacha Dhawan is a British actor known for his versatile television and film roles, including his acclaimed portrayal of the Master in the long-running sci-fi series Doctor Who.
-
E.
Aamir Khan
Aamir Khan is a renowned Indian film actor, director, and producer known for his critically acclaimed and socially impactful movies in Bollywood.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc9272cf4819089be118c8a49d7f9 |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3edc63c8190ac6737bf28993f1b |
completed | March 9, 2026, 11:50 a.m. |
Created at: March 4, 2026, 7:58 p.m.