Triple
T21944180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angrezi Medium |
E541893
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Kareena Kapoor Khan |
—
|
NE NERFINISHED |
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: Kareena Kapoor Khan | Statement: [Angrezi Medium, starring, Kareena Kapoor Khan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kareena Kapoor Khan Context triple: [Angrezi Medium, starring, Kareena Kapoor Khan]
-
A.
Kareena Kapoor Khan
chosen
Kareena Kapoor Khan is a prominent Indian film actress known for her versatile roles in Bollywood and her influential presence in contemporary Hindi cinema.
-
B.
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.
-
C.
Sonam Kapoor
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.
-
D.
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."
-
E.
Kangana Ranaut
Kangana Ranaut is an acclaimed Indian film actress known for her powerful performances in Hindi cinema and multiple National Film Awards.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.