Triple
T8154157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanjeev Bhaskar |
E190402
|
entity |
| Predicate | coStarredWith |
P14987
|
FINISHED |
| Object | Meera 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: Meera Syal | Statement: [Sanjeev Bhaskar, coStarredWith, Meera Syal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meera Syal Context triple: [Sanjeev Bhaskar, coStarredWith, Meera 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.
Reeta Chakrabarti
Reeta Chakrabarti is a British journalist, newsreader, and correspondent best known for her work with BBC News.
-
D.
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.
-
E.
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."
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb44d566b08190a6bb672f9c368806 |
completed | March 31, 2026, 3:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cced43a5448190b2600cbdbabf9d31 |
completed | April 1, 2026, 10:02 a.m. |
Created at: March 30, 2026, 5:37 p.m.