Triple
T21944385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haasil |
E541897
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Hrishitaa Bhatt |
—
|
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: Hrishitaa Bhatt | Statement: [Haasil, hasCastMember, Hrishitaa Bhatt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hrishitaa Bhatt Context triple: [Haasil, hasCastMember, Hrishitaa Bhatt]
-
A.
Hrishitaa Bhatt
chosen
Hrishitaa Bhatt is an Indian actress and model known for her work in Hindi films, particularly in the early 2000s.
-
B.
Geetika Jain
Geetika Jain is known as the wife of the late Anshu Jain, the former co-CEO of Deutsche Bank.
-
C.
Shivani Rawat
Shivani Rawat is an Indian-American film producer and founder of ShivHans Pictures, known for backing acclaimed independent films such as Trumbo and Captain Fantastic.
-
D.
Rima Jain
Rima Jain is an Indian film industry personality and member of the prominent Kapoor family, known as the daughter of legendary actor-filmmaker Raj Kapoor.
-
E.
Anisha Dadia
Anisha Dadia is a voice actor and audiobook narrator known for narrating Naomi Novik’s fantasy novel *A Deadly Education*.
- 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.