Triple
T21944590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karwaan |
E541902
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object |
Anurag Saikia
Anurag Saikia is an Indian music composer and producer known for his work on Hindi films and independent music projects.
|
E1525564
|
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: Anurag Saikia | Statement: [Karwaan, musicBy, Anurag Saikia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anurag Saikia Context triple: [Karwaan, musicBy, Anurag Saikia]
-
A.
Gautam Saha
Gautam Saha is a relatively obscure individual about whom no widely known public information is available.
-
B.
Ashutosh Rana
Ashutosh Rana is an acclaimed Indian film and television actor known for his intense character roles and powerful villainous performances in Hindi and regional cinema.
-
C.
Samit Bhanja
Samit Bhanja was an Indian film and theatre actor known for his work in Bengali cinema during the 1960s and 1970s.
-
D.
Sourav Pal
Sourav Pal is an accomplished Indian chemist and academic known for his contributions to theoretical and computational chemistry.
-
E.
Gaurav Shukla
Gaurav Shukla is an Indian screenwriter known for his work on Hindi films, including the comedy-drama "Angrezi Medium."
- 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: Anurag Saikia Triple: [Karwaan, musicBy, Anurag Saikia]
Generated description
Anurag Saikia is an Indian music composer and producer known for his work on Hindi films and independent music projects.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anurag Saikia Target entity description: Anurag Saikia is an Indian music composer and producer known for his work on Hindi films and independent music projects.
-
A.
Gautam Saha
Gautam Saha is a relatively obscure individual about whom no widely known public information is available.
-
B.
Ashutosh Rana
Ashutosh Rana is an acclaimed Indian film and television actor known for his intense character roles and powerful villainous performances in Hindi and regional cinema.
-
C.
Samit Bhanja
Samit Bhanja was an Indian film and theatre actor known for his work in Bengali cinema during the 1960s and 1970s.
-
D.
Sourav Pal
Sourav Pal is an accomplished Indian chemist and academic known for his contributions to theoretical and computational chemistry.
-
E.
Gaurav Shukla
Gaurav Shukla is an Indian screenwriter known for his work on Hindi films, including the comedy-drama "Angrezi Medium."
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242688988190a7b8f033c49368de |
completed | April 28, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0aae57ea5c81909003d0c6da529fbf |
completed | May 18, 2026, 6:14 a.m. |
| NEDg | Description generation | batch_6a0aaf0f47948190b602d1016badc21c |
completed | May 18, 2026, 6:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ab0befa5481909d00cb845dd67b12 |
completed | May 18, 2026, 6:25 a.m. |
Created at: April 16, 2026, 7:56 p.m.