Triple
T13410261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikita Gill |
E320067
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Nikita Gill |
E320067
|
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: Nikita Gill | Statement: [Nikita Gill, name, Nikita Gill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nikita Gill Context triple: [Nikita Gill, name, Nikita Gill]
-
A.
Nikita Gill
chosen
Nikita Gill is a contemporary British-Indian poet and writer known for her emotionally resonant, feminist poetry and modern retellings of myths and fairy tales.
-
B.
Ritika Sajdeh
Ritika Sajdeh is an Indian sports manager and public figure best known for her association with prominent cricketers and her marriage to Indian cricket star Rohit Sharma.
-
C.
Ambika Suri
Ambika Suri is known as the wife of Indian actor and producer Sanjay Suri.
-
D.
Sobhita Dhulipala
Sobhita Dhulipala is an Indian actress and former model known for her work in Hindi cinema and streaming series such as "Made in Heaven."
-
E.
Kajal Gupta
Kajal Gupta is an actress known for her work in Tollywood, the Bengali-language film industry based in Kolkata.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb3facc819088c1af3b59237e7a |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7307ccff08190aa4037aa5a48f7d0 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:35 p.m.