Triple
T16235876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rani Mukerji |
E394109
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Rani Mukherjee |
E394109
|
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: Rani Mukherjee | Statement: [Rani Mukerji, birthName, Rani Mukherjee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rani Mukherjee Context triple: [Rani Mukerji, birthName, Rani Mukherjee]
-
A.
Rani Mukerji
chosen
Rani Mukerji is an acclaimed Indian film actress known for her versatile performances in numerous successful Hindi movies since the late 1990s.
-
B.
Sushmita Sen
Sushmita Sen is an Indian actress, model, and the winner of the Miss Universe 1994 pageant, known for being the first Indian woman to win the title.
-
C.
Vidya Balan
Vidya Balan is an acclaimed Indian actress known for her powerful performances in Hindi cinema and for pioneering strong, female-led films in Bollywood.
-
D.
Madhuri Mukherjee
Madhuri Mukherjee, better known by her stage name Madhabi Mukherjee, is a renowned Indian Bengali film actress celebrated for her work in classic art-house cinema, including collaborations with director Satyajit Ray.
-
E.
Riya Sen
Riya Sen is an Indian actress and model known for her work in Hindi, Bengali, and other regional films, as well as for her prominent presence in Indian popular culture and fashion.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2455abc608190ba3308c15c9e8a23 |
completed | April 17, 2026, 2:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00354a20d081908288fb8c0e8b83b6 |
completed | May 10, 2026, 7:35 a.m. |
Created at: April 10, 2026, 5:04 a.m.