Triple
T11102641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raj Kapoor |
E262550
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ranbir |
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 | Statement: [Raj Kapoor, givenName, Ranbir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ranbir Context triple: [Raj Kapoor, givenName, Ranbir]
-
A.
Ranbir Kapoor
chosen
Ranbir Kapoor is a prominent Indian film actor and producer known for his leading roles in contemporary Hindi cinema.
-
B.
Ranveer Singh
Ranveer Singh is a popular Indian film actor known for his energetic performances and leading roles in numerous successful Bollywood movies.
-
C.
Rajkummar Rao
Rajkummar Rao is an acclaimed Indian film actor known for his versatile performances in Hindi cinema, particularly in critically praised independent and mainstream films.
-
D.
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."
-
E.
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."
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a2c30a481908c45020c37caebe4 |
completed | April 9, 2026, 12:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4833c0fdc8190935ae33eefae8e0c |
completed | April 19, 2026, 7:24 a.m. |
Created at: April 8, 2026, 9:27 p.m.