Triple
T22075651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamal Amrohi |
E545514
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Pakeezah
Pakeezah is a landmark 1972 Indian Hindi-language musical drama film celebrated for its poetic storytelling, iconic music, and Meena Kumari’s legendary performance.
|
E1518601
|
NE FINISHED |
How this triple was built (4 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: Pakeezah | Statement: [Kamal Amrohi, notableWork, Pakeezah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pakeezah Context triple: [Kamal Amrohi, notableWork, Pakeezah]
-
A.
Dilwaala
Dilwaala is an Indian film best known for featuring actress Persis Khambatta in a notable role.
-
B.
Gulaal
Gulaal is a 2009 Indian political drama film directed by Anurag Kashyap that explores themes of power, student politics, and separatism in Rajasthan.
-
C.
Mardaani
Mardaani is a 2014 Indian crime thriller film that follows a tough female police officer’s pursuit of a child trafficking racket.
-
D.
Jaanbaaz
Jaanbaaz is a 1986 Indian action-romance film directed by Feroz Khan, known for its stylish presentation, star-studded cast, and memorable music.
-
E.
Aghaat
Aghaat is a 1985 Hindi political drama film directed by Govind Nihalani, known for its intense portrayal of trade union politics and social conflict.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pakeezah Triple: [Kamal Amrohi, notableWork, Pakeezah]
Generated description
Pakeezah is a landmark 1972 Indian Hindi-language musical drama film celebrated for its poetic storytelling, iconic music, and Meena Kumari’s legendary performance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pakeezah Target entity description: Pakeezah is a landmark 1972 Indian Hindi-language musical drama film celebrated for its poetic storytelling, iconic music, and Meena Kumari’s legendary performance.
-
A.
Dilwaala
Dilwaala is an Indian film best known for featuring actress Persis Khambatta in a notable role.
-
B.
Gulaal
Gulaal is a 2009 Indian political drama film directed by Anurag Kashyap that explores themes of power, student politics, and separatism in Rajasthan.
-
C.
Mardaani
Mardaani is a 2014 Indian crime thriller film that follows a tough female police officer’s pursuit of a child trafficking racket.
-
D.
Jaanbaaz
Jaanbaaz is a 1986 Indian action-romance film directed by Feroz Khan, known for its stylish presentation, star-studded cast, and memorable music.
-
E.
Aghaat
Aghaat is a 1985 Hindi political drama film directed by Govind Nihalani, known for its intense portrayal of trade union politics and social conflict.
- F. None of above. chosen
Provenance (5 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b1904881909a1769ce8be39e05 |
completed | April 28, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a8793a1ec8190977047d2c094845d |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a8a706f8481908e3c09c936948576 |
completed | May 18, 2026, 3:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a8aeed53c8190a261573a43a03929 |
completed | May 18, 2026, 3:43 a.m. |
Created at: April 16, 2026, 8:28 p.m.