Triple
T21944492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 7 Khoon Maaf |
E541900
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Annu Kapoor |
—
|
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: Annu Kapoor | Statement: [7 Khoon Maaf, starring, Annu Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Annu Kapoor Context triple: [7 Khoon Maaf, starring, Annu Kapoor]
-
A.
Annu Kapoor
chosen
Annu Kapoor is an Indian film and television actor, radio host, and television presenter known for his character roles and work on shows like "Antakshari."
-
B.
Shakti Kapoor
Shakti Kapoor is a veteran Indian film actor best known for his comic and villainous roles in numerous Bollywood movies since the late 1970s.
-
C.
Shalini Kapoor
Shalini Kapoor is an Indian television and film actress known for her character roles in popular Hindi TV serials and movies.
-
D.
Neetu Kapoor
Neetu Kapoor is an Indian film actress best known for her work in Hindi cinema from the 1970s and 1980s and for being part of the prominent Kapoor film family.
-
E.
Anjali Apte
Anjali Apte is a notable individual associated with the surname Apte, recognized for her contributions in her respective field.
- 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.