Triple
T21428499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Thursday |
E528622
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Neha Dhupia |
—
|
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: Neha Dhupia | Statement: [A Thursday, castMember, Neha Dhupia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neha Dhupia Context triple: [A Thursday, castMember, Neha Dhupia]
-
A.
Neha Dhupia
chosen
Neha Dhupia is an Indian actress and former Miss India who has appeared in numerous Bollywood films and television shows.
-
B.
Meghna Kapoor
Meghna Kapoor is known as the wife of Indian actor and filmmaker Rajat Kapoor.
-
C.
Divya Katdare
Divya Katdare is a central character on the television series "Royal Pains," known as a skilled and poised physician assistant who works closely with concierge doctor Hank Lawson in the Hamptons.
-
D.
Bhumika Chawla
Bhumika Chawla is an Indian actress known for her work in Hindi, Telugu, and Tamil films, including notable roles in movies like "Tere Naam" and "Gandhi, My Father."
-
E.
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."
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b3e74bcc81909ad66e3c59152ffc |
completed | April 22, 2026, 11:41 a.m. |
Created at: April 16, 2026, 5:49 p.m.