Triple
T21944755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virasat |
E541906
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Pooja Batra
Pooja Batra is an Indian actress and former model best known for her work in Hindi cinema during the 1990s and early 2000s.
|
E1521601
|
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 Batra | Statement: [Virasat, stars, Pooja Batra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pooja Batra Context triple: [Virasat, stars, Pooja Batra]
-
A.
Anjana Patel
Anjana Patel is a member of a specific subgroup within the broader Patel community, traditionally associated with agrarian and mercantile occupations in India.
-
B.
Shefali Chowdhury
Shefali Chowdhury is a British actress best known for playing Parvati Patil in the Harry Potter film series.
-
C.
Pallavi Joshi
Pallavi Joshi is an acclaimed Indian actress and producer known for her nuanced performances in parallel cinema and television, as well as for winning multiple National Film Awards.
-
D.
Kajal Gupta
Kajal Gupta is an actress known for her work in Tollywood, the Bengali-language film industry based in Kolkata.
-
E.
Anuja Joshi
Anuja Joshi is an Indian-American actress known for her roles in television dramas and web series, including prominent work in both Indian and American productions.
- 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 Batra Triple: [Virasat, stars, Pooja Batra]
Generated description
Pooja Batra is an Indian actress and former model best known for her work in Hindi cinema during the 1990s and early 2000s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pooja Batra Target entity description: Pooja Batra is an Indian actress and former model best known for her work in Hindi cinema during the 1990s and early 2000s.
-
A.
Anjana Patel
Anjana Patel is a member of a specific subgroup within the broader Patel community, traditionally associated with agrarian and mercantile occupations in India.
-
B.
Shefali Chowdhury
Shefali Chowdhury is a British actress best known for playing Parvati Patil in the Harry Potter film series.
-
C.
Pallavi Joshi
Pallavi Joshi is an acclaimed Indian actress and producer known for her nuanced performances in parallel cinema and television, as well as for winning multiple National Film Awards.
-
D.
Kajal Gupta
Kajal Gupta is an actress known for her work in Tollywood, the Bengali-language film industry based in Kolkata.
-
E.
Anuja Joshi
Anuja Joshi is an Indian-American actress known for her roles in television dramas and web series, including prominent work in both Indian and American productions.
- 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_6a0a96e5e0308190a6dc4c4d5192b774 |
completed | May 18, 2026, 4:34 a.m. |
| NEDg | Description generation | batch_6a0a98873d44819099d861571a21bb4e |
completed | May 18, 2026, 4:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a990173b88190ae92852b24456e85 |
completed | May 18, 2026, 4:43 a.m. |
Created at: April 16, 2026, 7:56 p.m.