Triple
T21944054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lunchbox |
E541890
|
entity |
| Predicate | leadActorRole |
P5563
|
FINISHED |
| Object | Irrfan Khan as Saajan Fernandes |
—
|
NE NERFINISHED |
How this triple was built (3 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: Irrfan Khan as Saajan Fernandes | Statement: [The Lunchbox, leadActorRole, Irrfan Khan as Saajan Fernandes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Irrfan Khan as Saajan Fernandes Context triple: [The Lunchbox, leadActorRole, Irrfan Khan as Saajan Fernandes]
-
A.
Anupam Kher as Dr. Cliff Patel
Anupam Kher as Dr. Cliff Patel is the portrayal of a compassionate and insightful therapist who helps guide the protagonist’s emotional recovery in the film "Silver Linings Playbook."
-
B.
Shah Rukh Khan as Amar Varma
Shah Rukh Khan as Amar Varma is the intense, idealistic All India Radio journalist at the heart of the romantic political thriller "Dil Se..," whose obsessive love story unfolds against a backdrop of insurgency and unrest in Northeast India.
-
C.
Rizwan Khan from My Name Is Khan
Rizwan Khan from *My Name Is Khan* is a gentle, autistic Muslim man who embarks on a cross-country journey in the United States to challenge prejudice and clear his name after being wrongfully associated with terrorism.
-
D.
Daru Shezad
Daru Shezad is the disillusioned, downward-spiraling protagonist of Mohsin Hamid’s novel "Moth Smoke," set against the backdrop of contemporary Lahore’s social and economic inequalities.
-
E.
Michael Ansara
Michael Ansara was a Syrian-American character actor best known for his deep voice and frequent roles in Westerns and science fiction, including memorable appearances in series like Star Trek and Babylon 5.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Irrfan Khan as Saajan Fernandes Target entity description: Irrfan Khan as Saajan Fernandes is the quietly lonely, middle-aged office worker at the heart of the film "The Lunchbox," whose unexpected epistolary relationship with a stranger transforms his routine life.
-
A.
Anupam Kher as Dr. Cliff Patel
Anupam Kher as Dr. Cliff Patel is the portrayal of a compassionate and insightful therapist who helps guide the protagonist’s emotional recovery in the film "Silver Linings Playbook."
-
B.
Shah Rukh Khan as Amar Varma
Shah Rukh Khan as Amar Varma is the intense, idealistic All India Radio journalist at the heart of the romantic political thriller "Dil Se..," whose obsessive love story unfolds against a backdrop of insurgency and unrest in Northeast India.
-
C.
Rizwan Khan from My Name Is Khan
Rizwan Khan from *My Name Is Khan* is a gentle, autistic Muslim man who embarks on a cross-country journey in the United States to challenge prejudice and clear his name after being wrongfully associated with terrorism.
-
D.
Daru Shezad
Daru Shezad is the disillusioned, downward-spiraling protagonist of Mohsin Hamid’s novel "Moth Smoke," set against the backdrop of contemporary Lahore’s social and economic inequalities.
-
E.
Michael Ansara
Michael Ansara was a Syrian-American character actor best known for his deep voice and frequent roles in Westerns and science fiction, including memorable appearances in series like Star Trek and Babylon 5.
- F. None of above. chosen
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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242515ec8190b015bf8c7b13be85 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:56 p.m.