Triple
T10523540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latika |
E248235
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Tanvi Ganesh Lonkar
Tanvi Ganesh Lonkar is an Indian actress best known for playing the teenage version of Latika in the Academy Award–winning film "Slumdog Millionaire."
|
E871260
|
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: Tanvi Ganesh Lonkar | Statement: [Latika, portrayedBy, Tanvi Ganesh Lonkar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tanvi Ganesh Lonkar Context triple: [Latika, portrayedBy, Tanvi Ganesh Lonkar]
-
A.
Shivani Rawat
Shivani Rawat is an Indian-American film producer and founder of ShivHans Pictures, known for backing acclaimed independent films such as Trumbo and Captain Fantastic.
-
B.
Shaan Hathiramani
Shaan Hathiramani is an entrepreneur best known as a co-founder of the mobile video-sharing app Socialcam.
-
C.
Jyoti Devlalikar
Jyoti Devlalikar is a character in the Indian television series "Kanyadaan."
-
D.
Anju Mallige
Anju Mallige is a notable work by acclaimed Indian playwright and filmmaker Girish Karnad.
-
E.
Gitali Roy
Gitali Roy was an Indian actress best known for her role in Satyajit Ray’s acclaimed Bengali film "Charulata."
- 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: Tanvi Ganesh Lonkar Triple: [Latika, portrayedBy, Tanvi Ganesh Lonkar]
Generated description
Tanvi Ganesh Lonkar is an Indian actress best known for playing the teenage version of Latika in the Academy Award–winning film "Slumdog Millionaire."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tanvi Ganesh Lonkar Target entity description: Tanvi Ganesh Lonkar is an Indian actress best known for playing the teenage version of Latika in the Academy Award–winning film "Slumdog Millionaire."
-
A.
Shivani Rawat
Shivani Rawat is an Indian-American film producer and founder of ShivHans Pictures, known for backing acclaimed independent films such as Trumbo and Captain Fantastic.
-
B.
Shaan Hathiramani
Shaan Hathiramani is an entrepreneur best known as a co-founder of the mobile video-sharing app Socialcam.
-
C.
Jyoti Devlalikar
Jyoti Devlalikar is a character in the Indian television series "Kanyadaan."
-
D.
Anju Mallige
Anju Mallige is a notable work by acclaimed Indian playwright and filmmaker Girish Karnad.
-
E.
Gitali Roy
Gitali Roy was an Indian actress best known for her role in Satyajit Ray’s acclaimed Bengali film "Charulata."
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509e155b08190996325bf484ec55d |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d933f2d9e48190a4c5d5d5bdc0d7d8 |
completed | April 10, 2026, 5:31 p.m. |
| NEDg | Description generation | batch_69d938c697f481908a93296ee7f82eae |
completed | April 10, 2026, 5:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d940176c988190b7583ce9f2c21898 |
completed | April 10, 2026, 6:23 p.m. |
Created at: April 6, 2026, 12:29 p.m.