Triple
T16183350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jo Jeeta Wohi Sikandar |
E392738
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Pooja Bedi
Pooja Bedi is an Indian actress and television personality best known for her roles in popular 1990s Bollywood films and her appearances on reality TV shows.
|
E1203559
|
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: Pooja Bedi | Statement: [Jo Jeeta Wohi Sikandar, starring, Pooja Bedi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pooja Bedi Context triple: [Jo Jeeta Wohi Sikandar, starring, Pooja Bedi]
-
A.
Anuradha Paudwal
Anuradha Paudwal is a renowned Indian playback and devotional singer celebrated for her extensive work in Hindi cinema and bhajans since the 1970s.
-
B.
Poonam Sinha
Poonam Sinha is an Indian actress and film producer known for her supporting roles in Hindi cinema and as the wife of veteran actor Shatrughan Sinha.
-
C.
Beena Pal
Beena Pal was the wife of Indian nationalist leader and freedom fighter Bipin Chandra Pal.
-
D.
Nandita Puri
Nandita Puri is an Indian journalist and author best known for her biography of her late husband, acclaimed actor Om Puri.
-
E.
Neena Gupta
Neena Gupta is an acclaimed Indian film, television, and theatre actress and director known for her versatile performances across parallel and mainstream cinema.
- 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: Pooja Bedi Triple: [Jo Jeeta Wohi Sikandar, starring, Pooja Bedi]
Generated description
Pooja Bedi is an Indian actress and television personality best known for her roles in popular 1990s Bollywood films and her appearances on reality TV shows.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pooja Bedi Target entity description: Pooja Bedi is an Indian actress and television personality best known for her roles in popular 1990s Bollywood films and her appearances on reality TV shows.
-
A.
Anuradha Paudwal
Anuradha Paudwal is a renowned Indian playback and devotional singer celebrated for her extensive work in Hindi cinema and bhajans since the 1970s.
-
B.
Poonam Sinha
Poonam Sinha is an Indian actress and film producer known for her supporting roles in Hindi cinema and as the wife of veteran actor Shatrughan Sinha.
-
C.
Beena Pal
Beena Pal was the wife of Indian nationalist leader and freedom fighter Bipin Chandra Pal.
-
D.
Nandita Puri
Nandita Puri is an Indian journalist and author best known for her biography of her late husband, acclaimed actor Om Puri.
-
E.
Neena Gupta
Neena Gupta is an acclaimed Indian film, television, and theatre actress and director known for her versatile performances across parallel and mainstream cinema.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205ef39081908da383abdebc2ccc |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0017a7223c81909f04144bdffb22ff |
completed | May 10, 2026, 5:29 a.m. |
| NEDg | Description generation | batch_6a00195984c881909483fbf2afb518d1 |
completed | May 10, 2026, 5:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0019cbdc64819092184420bd4fd8ed |
completed | May 10, 2026, 5:38 a.m. |
Created at: April 10, 2026, 5:02 a.m.