Triple
T21944216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talvar |
E541894
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Meghna Gulzar |
—
|
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: Meghna Gulzar | Statement: [Talvar, director, Meghna Gulzar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meghna Gulzar Context triple: [Talvar, director, Meghna Gulzar]
-
A.
Meghna Gulzar
chosen
Meghna Gulzar is an Indian film director and screenwriter known for critically acclaimed Hindi films such as "Talvar," "Raazi," and "Chhapaak."
-
B.
Sakina Ansari
Sakina Ansari is a daughter of the acclaimed American playwright August Wilson.
-
C.
Nadira Babbar
Nadira Babbar is an Indian theatre director and actress known for her work in Hindi cinema and on stage, including a role in the film "Bride and Prejudice."
-
D.
Rupa Mehra
Rupa Mehra is a central matriarchal figure in Vikram Seth’s novel "A Suitable Boy," best known for her determined quest to find an ideal husband for her daughter Lata.
-
E.
Lata Mehra
Lata Mehra is the young, strong-willed protagonist of Vikram Seth’s novel "A Suitable Boy," whose search for love and independence unfolds against the backdrop of post-independence India.
- 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.