Triple
T10213107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rockstar |
E242377
|
entity |
| Predicate | leadActor |
P1507
|
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: [Rockstar, leadActor, Ranbir Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ranbir Kapoor Context triple: [Rockstar, leadActor, 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.
Ranveer Singh
Ranveer Singh is a popular Indian film actor known for his energetic performances and leading roles in numerous successful Bollywood movies.
-
C.
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."
-
D.
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.
-
E.
Rajat Kapoor
Rajat Kapoor is an Indian actor, writer, and filmmaker known for his work in independent cinema and acclaimed films such as "Bheja Fry," "Mithya," and "Ankhon Dekhi."
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa24efc081909714d98943543283 |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f6f4d0cc8190ae41277b15b3012d |
completed | April 9, 2026, 12:46 a.m. |
Created at: April 6, 2026, 11:03 a.m.