Triple
T10354224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anil Kapoor |
E243955
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Janhvi Kapoor |
E743343
|
NE FINISHED |
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: Janhvi Kapoor | Statement: [Anil Kapoor, relative, Janhvi Kapoor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Janhvi Kapoor Context triple: [Anil Kapoor, relative, Janhvi Kapoor]
-
A.
Janhvi Kapoor
chosen
Janhvi Kapoor is an Indian film actress who works primarily in Hindi cinema and is known for being one of the prominent young stars in Bollywood.
-
B.
Syesha Kapoor
Syesha Kapoor is the daughter of renowned Indian playback singer Alka Yagnik.
-
C.
Shriya Saran
Shriya Saran is an Indian actress and model known for her work in Telugu, Tamil, and Hindi cinema, appearing in numerous commercially successful and critically acclaimed films.
-
D.
Aditi Rao Hydari
Aditi Rao Hydari is an Indian actress and classical dancer known for her work in Hindi, Tamil, Telugu, and Malayalam films, often praised for her expressive performances and graceful screen presence.
-
E.
Shefali Shah
Shefali Shah is an acclaimed Indian actress known for her powerful performances in film, television, and streaming series such as "Satya," "Dil Dhadakne Do," and "Delhi Crime."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e952c878819084e5d7a593a3f9e9 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e64109881908c42a4fbcfd057be |
completed | April 10, 2026, 4:36 a.m. |
Created at: April 6, 2026, 11:58 a.m.