Triple
T11102560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapoor |
E262548
|
entity |
| Predicate | notableBearer |
P458
|
FINISHED |
| Object | Sonam Kapoor |
E266068
|
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: Sonam Kapoor | Statement: [Kapoor, notableBearer, Sonam Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sonam Kapoor Context triple: [Kapoor, notableBearer, Sonam Kapoor]
-
A.
Sonam Kapoor
chosen
Sonam Kapoor is a prominent Indian actress and fashion icon known for her work in Hindi cinema and her influential presence in the fashion industry.
-
B.
Anushka Sharma
Anushka Sharma is a prominent Indian actress and film producer known for her work in Bollywood films such as "Rab Ne Bana Di Jodi," "PK," and "NH10."
-
C.
Kareena Kapoor Khan
Kareena Kapoor Khan is a prominent Indian film actress known for her versatile roles in Bollywood and her influential presence in contemporary Hindi cinema.
-
D.
Anushka Shetty
Anushka Shetty is a prominent Indian actress best known for her leading roles in Telugu and Tamil cinema, including major historical and fantasy epics.
-
E.
Deepika Padukone
Deepika Padukone is a leading Indian film actress and producer, internationally recognized for her work in Bollywood and Hollywood as well as her advocacy for mental health awareness.
- 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_69e3e7f9b46881909761ed448fa5ce6e |
completed | April 18, 2026, 8:22 p.m. |
Created at: April 8, 2026, 9:27 p.m.