Triple
T21428707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krantiveer |
E528626
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Megha Dixit
Megha Dixit is a central female character in the 1994 Hindi film "Krantiveer," known for her strong-willed and emotionally intense role in the story’s fight against injustice.
|
E1494443
|
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: Megha Dixit | Statement: [Krantiveer, character, Megha Dixit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Megha Dixit Context triple: [Krantiveer, character, Megha Dixit]
-
A.
Namrata Dutt
Namrata Dutt is an Indian public figure best known as the daughter of legendary Bollywood actor-politician Sunil Dutt and sister of actor Sanjay Dutt.
-
B.
Smriti Malhotra
Smriti Malhotra is an Indian politician, former television actress, and current Union Minister better known by her married name, Smriti Irani.
-
C.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
-
D.
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.
-
E.
Divya Dutta
Divya Dutta is an Indian film actress known for her versatile supporting and character roles across Hindi and Punjabi 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: Megha Dixit Triple: [Krantiveer, character, Megha Dixit]
Generated description
Megha Dixit is a central female character in the 1994 Hindi film "Krantiveer," known for her strong-willed and emotionally intense role in the story’s fight against injustice.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Megha Dixit Target entity description: Megha Dixit is a central female character in the 1994 Hindi film "Krantiveer," known for her strong-willed and emotionally intense role in the story’s fight against injustice.
-
A.
Namrata Dutt
Namrata Dutt is an Indian public figure best known as the daughter of legendary Bollywood actor-politician Sunil Dutt and sister of actor Sanjay Dutt.
-
B.
Smriti Malhotra
Smriti Malhotra is an Indian politician, former television actress, and current Union Minister better known by her married name, Smriti Irani.
-
C.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
-
D.
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.
-
E.
Divya Dutta
Divya Dutta is an Indian film actress known for her versatile supporting and character roles across Hindi and Punjabi 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee813db52c8190ac933bc6ec4dbf77 |
completed | April 26, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a0f7f236081909986f17b2fbb1ddb |
completed | May 17, 2026, 6:57 p.m. |
| NEDg | Description generation | batch_6a0a10106ab4819096045effbbdfe95e |
completed | May 17, 2026, 6:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a10c8c5bc8190add0ee63eb338964 |
completed | May 17, 2026, 7:02 p.m. |
Created at: April 16, 2026, 5:49 p.m.