Triple
T8189885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meera Syal |
E191276
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Feroza Syal |
E191276
|
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: Feroza Syal | Statement: [Meera Syal, birthName, Feroza Syal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Feroza Syal Context triple: [Meera Syal, birthName, Feroza Syal]
-
A.
Meera Syal
chosen
Meera Syal is a British comedian, writer, playwright, and actress known for her work on "Goodness Gracious Me," "The Kumars at No. 42," and numerous stage and screen roles.
-
B.
Reema Lagoo
Reema Lagoo was a prominent Indian film, television, and theatre actress best known for playing iconic motherly roles in Hindi and Marathi cinema.
-
C.
Persis Khambatta
Persis Khambatta was an Indian model and actress best known internationally for her role as Lieutenant Ilia in "Star Trek: The Motion Picture."
-
D.
Afroza Azad
Afroza Azad is best known as the wife of prominent Bangladeshi writer, linguist, and intellectual Humayun Azad.
-
E.
Salma Lakhani
Salma Lakhani is a Canadian businesswoman and philanthropist who became the first Muslim and first South Asian to serve as a lieutenant governor in Canada.
- 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_69ca82c5b6948190a583c096fb0a6c71 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4da0e1288190b9c7c1d3b9a98830 |
completed | March 31, 2026, 4:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd94bbdc288190aee5187e95ca7a8d |
completed | April 1, 2026, 9:57 p.m. |
Created at: March 30, 2026, 5:41 p.m.