Triple
T22951752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anuradha Paudwal |
E570037
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object |
Aditya Paudwal
Aditya Paudwal was an Indian music arranger and producer, known for his work in devotional and film music and as the son of renowned playback singer Anuradha Paudwal.
|
E1563496
|
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: Aditya Paudwal | Statement: [Anuradha Paudwal, hasRelative, Aditya Paudwal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aditya Paudwal Context triple: [Anuradha Paudwal, hasRelative, Aditya Paudwal]
-
A.
Shubham Saraf
Shubham Saraf is a British actor known for his role in the TV crime drama "Criminal: UK" and performances across film, television, and theatre.
-
B.
Aditya Sood
Aditya Sood is a film producer known for his work on high-profile Hollywood projects, including the thriller-comedy "Cocaine Bear."
-
C.
Aditya Patel
Aditya Patel is a character from the Indian political drama film "Hu Tu Tu."
-
D.
Shreyas Jain
Shreyas Jain is an Indian screenwriter best known for co-writing the critically acclaimed and commercially successful Bollywood film "Dangal."
-
E.
Akarsh Khurana
Akarsh Khurana is an Indian filmmaker, writer, and actor known for his work in contemporary Hindi cinema and theatre.
- 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: Aditya Paudwal Triple: [Anuradha Paudwal, hasRelative, Aditya Paudwal]
Generated description
Aditya Paudwal was an Indian music arranger and producer, known for his work in devotional and film music and as the son of renowned playback singer Anuradha Paudwal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aditya Paudwal Target entity description: Aditya Paudwal was an Indian music arranger and producer, known for his work in devotional and film music and as the son of renowned playback singer Anuradha Paudwal.
-
A.
Shubham Saraf
Shubham Saraf is a British actor known for his role in the TV crime drama "Criminal: UK" and performances across film, television, and theatre.
-
B.
Aditya Sood
Aditya Sood is a film producer known for his work on high-profile Hollywood projects, including the thriller-comedy "Cocaine Bear."
-
C.
Aditya Patel
Aditya Patel is a character from the Indian political drama film "Hu Tu Tu."
-
D.
Shreyas Jain
Shreyas Jain is an Indian screenwriter best known for co-writing the critically acclaimed and commercially successful Bollywood film "Dangal."
-
E.
Akarsh Khurana
Akarsh Khurana is an Indian filmmaker, writer, and actor known for his work in contemporary Hindi cinema and theatre.
- 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181a285448190a718734fe933d51a |
completed | April 29, 2026, 3:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bca17e51881909f147ae8677e2a90 |
completed | May 19, 2026, 2:25 a.m. |
| NEDg | Description generation | batch_6a0bcaebed688190b2ea74c588922d98 |
completed | May 19, 2026, 2:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bcbec354081909dbeeb389e86d38c |
completed | May 19, 2026, 2:33 a.m. |
Created at: April 17, 2026, 3:46 p.m.