Triple
T21944075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haider |
E541891
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Basharat Peer |
—
|
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: Basharat Peer | Statement: [Haider, screenwriter, Basharat Peer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Basharat Peer Context triple: [Haider, screenwriter, Basharat Peer]
-
A.
Basharat Peer
chosen
Basharat Peer is an Indian journalist and author best known for his writings on Kashmir, including the acclaimed memoir "Curfewed Night."
-
B.
Arsher Ali
Arsher Ali is a British actor known for his work in film, television, and theatre, including roles in projects such as the horror film "The Ritual."
-
C.
Rehan Siddiqui
Rehan Siddiqui is a British climbing and mountaineering leader who has served as president of the British Mountaineering Council, the national representative body for climbers, hill walkers, and mountaineers in Britain.
-
D.
Shahid Azeem
Shahid Azeem is a British-Pakistani businessman and football executive best known for his leadership role at Aldershot Town Football Club.
-
E.
Shaheen Khan
Shaheen Khan is a British actress best known for her role as the protagonist’s mother in the hit film "Bend It Like Beckham."
- 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_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.