Triple
T21097219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leila Hatami |
E519798
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Leila Hatami |
—
|
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: Leila Hatami | Statement: [Leila Hatami, name, Leila Hatami]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leila Hatami Context triple: [Leila Hatami, name, Leila Hatami]
-
A.
Leila Hatami
chosen
Leila Hatami is an acclaimed Iranian actress best known internationally for her award-winning role in the Oscar-winning film "A Separation."
-
B.
Parvin Ardalan
Parvin Ardalan is an Iranian feminist writer and human rights activist known for her leading role in Iran’s women’s rights movement.
-
C.
Hedieh Tehrani
Hedieh Tehrani is a prominent Iranian film actress acclaimed for her intense, nuanced performances in contemporary Iranian cinema.
-
D.
Marzieh Meshkini
Marzieh Meshkini is an Iranian film director and screenwriter known for her socially conscious, visually poetic works within contemporary Iranian cinema.
-
E.
Shahrzad Davani
Shahrzad Davani is a film producer best known for her work on the biographical drama "Brain on Fire."
- 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_69e0b508d8dc81909be940dafe36c8f7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e71b595cdc8190ba7a6f3f71d40c3f |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 2:52 p.m.