Triple
T9909703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ranbir Kapoor |
E185108
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kapoor |
E50369
|
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: Kapoor | Statement: [Ranbir Kapoor, familyName, Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kapoor Context triple: [Ranbir Kapoor, familyName, Kapoor]
-
A.
Kapoor
chosen
Kapoor is a common Indian surname associated with a prominent Punjabi Khatri family, many of whose members have achieved fame in fields such as film, art, and business.
-
B.
Boney Kapoor
Boney Kapoor is a prominent Indian film producer known for backing numerous successful Bollywood and South Indian films.
-
C.
Randhir Kapoor
Randhir Kapoor is an Indian actor, director, and producer from the prominent Kapoor film family, known for his work in Hindi cinema since the 1970s.
-
D.
Pankaj Kapur
Pankaj Kapur is an acclaimed Indian actor and director known for his powerful performances in film, television, and theatre.
-
E.
Deepak Kapur
Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb51184d08190a0350f2722110811 |
completed | April 2, 2026, 12:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20db5979081909b8e292ac6bb7c2f |
completed | April 5, 2026, 7:22 a.m. |
Created at: March 30, 2026, 8:41 p.m.