Triple
T22111567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buniyaad |
E546429
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Anita Kanwar |
—
|
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: Anita Kanwar | Statement: [Buniyaad, starring, Anita Kanwar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anita Kanwar Context triple: [Buniyaad, starring, Anita Kanwar]
-
A.
Anita Kanwar
chosen
Anita Kanwar is an Indian actress best known for her acclaimed roles in parallel cinema and television, particularly the landmark TV series "Buniyaad."
-
B.
Anita Bhalla
Anita Bhalla is a British media executive and former BBC journalist known for her leadership roles in broadcasting and public service in the UK.
-
C.
Tarika Bansal
Tarika Bansal is the ambitious daughter of the protagonist in the Hindi film "Angrezi Medium," whose dream of studying abroad drives the emotional core of the story.
-
D.
Sarita Khurana
Sarita Khurana is a filmmaker and producer known for her work on culturally focused, immigrant-centered stories in film and television.
-
E.
Neela Rasgotra
Neela Rasgotra is a fictional surgical resident and later attending physician on the medical drama series "ER," known for her intelligence, compassion, and complex personal relationships.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12949cc7881908898ca7dc130f57f |
completed | April 28, 2026, 9:40 p.m. |
Created at: April 16, 2026, 8:31 p.m.