Triple
T10354110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freida Pinto |
E243953
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Freida Pinto |
E243953
|
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: Freida Pinto | Statement: [Freida Pinto, name, Freida Pinto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freida Pinto Context triple: [Freida Pinto, name, Freida Pinto]
-
A.
Freida Pinto
chosen
Freida Pinto is an Indian actress and model who gained international recognition for her breakout role in the Academy Award–winning film "Slumdog Millionaire."
-
B.
Kiran Rao
Kiran Rao is an Indian film producer, director, and screenwriter known for her work in Hindi cinema and for co-producing acclaimed films such as "Dhobi Ghat" and "Delhi Belly."
-
C.
Konkona Sen Sharma
Konkona Sen Sharma is an acclaimed Indian actress and filmmaker known for her powerful performances in parallel and mainstream Hindi and Bengali cinema.
-
D.
Carmen Ejogo
Carmen Ejogo is a British actress and singer known for her versatile film and television roles, including her acclaimed portrayal of Coretta Scott King in the historical drama "Selma."
-
E.
Rooney Mara
Rooney Mara is an American actress known for her acclaimed performances in films such as "The Girl with the Dragon Tattoo" and "Carol."
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e952c878819084e5d7a593a3f9e9 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d750a30af88190b2ebf0daf758ed44 |
completed | April 9, 2026, 7:09 a.m. |
Created at: April 6, 2026, 11:58 a.m.