Triple
T11022911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamal Bose |
E260534
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Anuraag
Anuraag is a 1972 Hindi romantic drama film directed by Shakti Samanta, known for its emotional story and popular music.
|
E900395
|
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: Anuraag | Statement: [Kamal Bose, notableWork, Anuraag]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anuraag Context triple: [Kamal Bose, notableWork, Anuraag]
-
A.
Anubhav
Anubhav is a Hindi-language film featuring actor Sanjay Suri in a significant role.
-
B.
Anjana
Anjana is a revered figure in Hindu mythology, best known as the mother of the monkey-god Hanuman and often depicted as a celestial nymph who took birth on earth.
-
C.
Savyasachi
Savyasachi is a celebrated epithet of the Mahabharata hero Arjuna, highlighting his legendary ambidextrous skill in archery and combat.
-
D.
Aniruddha
Aniruddha is a prominent figure in Hindu mythology, known as the grandson of Krishna and a heroic member of the Yadava dynasty.
-
E.
Arun
Arun is a local government district and borough in West Sussex, England, named after the River Arun and encompassing coastal towns such as Bognor Regis and Littlehampton.
- 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: Anuraag Triple: [Kamal Bose, notableWork, Anuraag]
Generated description
Anuraag is a 1972 Hindi romantic drama film directed by Shakti Samanta, known for its emotional story and popular music.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anuraag Target entity description: Anuraag is a 1972 Hindi romantic drama film directed by Shakti Samanta, known for its emotional story and popular music.
-
A.
Anubhav
Anubhav is a Hindi-language film featuring actor Sanjay Suri in a significant role.
-
B.
Anjana
Anjana is a revered figure in Hindu mythology, best known as the mother of the monkey-god Hanuman and often depicted as a celestial nymph who took birth on earth.
-
C.
Savyasachi
Savyasachi is a celebrated epithet of the Mahabharata hero Arjuna, highlighting his legendary ambidextrous skill in archery and combat.
-
D.
Aniruddha
Aniruddha is a prominent figure in Hindu mythology, known as the grandson of Krishna and a heroic member of the Yadava dynasty.
-
E.
Arun
Arun is a local government district and borough in West Sussex, England, named after the River Arun and encompassing coastal towns such as Bognor Regis and Littlehampton.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797bd88188190a644adc9283cabb8 |
completed | April 9, 2026, 12:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3750917d481909e73de0bfae27827 |
completed | April 18, 2026, 12:11 p.m. |
| NEDg | Description generation | batch_69e37ab860f48190808ba0076cfa9c98 |
completed | April 18, 2026, 12:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3864dd0d48190b3fd81381f5d7418 |
completed | April 18, 2026, 1:25 p.m. |
Created at: April 8, 2026, 9:25 p.m.