Triple
T21109491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mollywood |
E520135
|
entity |
| Predicate | hasNotableActor |
P17435
|
FINISHED |
| Object | Fahadh Faasil |
—
|
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: Fahadh Faasil | Statement: [Mollywood, hasNotableActor, Fahadh Faasil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fahadh Faasil Context triple: [Mollywood, hasNotableActor, Fahadh Faasil]
-
A.
Fahadh Faasil
chosen
Fahadh Faasil is an acclaimed Indian actor, primarily known for his versatile and intense performances in Malayalam cinema and notable roles in pan-Indian films.
-
B.
Nagi Hassan
Nagi Hassan is the primary antagonist and terrorist leader in the 1996 action-thriller film "Executive Decision."
-
C.
Khalid Ashraf
Khalid Ashraf is a computer scientist and deep learning researcher known for co-designing the efficient convolutional neural network architecture SqueezeNet.
-
D.
Moosa Mostafa
Moosa Mostafa is a young British actor best known for his role in the Netflix supernatural comedy-horror series "Wednesday."
-
E.
Salim Akil
Salim Akil is an American television and film director, writer, and producer best known for his work on projects like the TV series "Girlfriends," "The Game," and "Black Lightning."
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7210110a48190a6359b6732f6293d |
completed | April 21, 2026, 7:02 a.m. |
Created at: April 16, 2026, 2:54 p.m.