Triple
T8558972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enthiran |
E202643
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Aishwarya Rai
Aishwarya Rai is an acclaimed Indian actress and former Miss World, renowned for her work in Bollywood and international cinema as well as her iconic beauty.
|
E746029
|
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: Aishwarya Rai | Statement: [Enthiran, starring, Aishwarya Rai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aishwarya Rai Context triple: [Enthiran, starring, Aishwarya Rai]
-
A.
Lara Dutta
Lara Dutta is an Indian actress, model, and former Miss Universe (2000) known for her work in Bollywood films.
-
B.
Karisma Kapoor
Karisma Kapoor is an acclaimed Indian film actress best known for her leading roles in popular Hindi movies of the 1990s and early 2000s.
-
C.
Kareena Kapoor Khan
Kareena Kapoor Khan is a prominent Indian film actress known for her versatile roles in Bollywood and her influential presence in contemporary Hindi cinema.
-
D.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
-
E.
Deepika Padukone
Deepika Padukone is a leading Indian film actress and producer, internationally recognized for her work in Bollywood and Hollywood as well as her advocacy for mental health awareness.
- 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: Aishwarya Rai Triple: [Enthiran, starring, Aishwarya Rai]
Generated description
Aishwarya Rai is an acclaimed Indian actress and former Miss World, renowned for her work in Bollywood and international cinema as well as her iconic beauty.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aishwarya Rai Target entity description: Aishwarya Rai is an acclaimed Indian actress and former Miss World, renowned for her work in Bollywood and international cinema as well as her iconic beauty.
-
A.
Lara Dutta
Lara Dutta is an Indian actress, model, and former Miss Universe (2000) known for her work in Bollywood films.
-
B.
Karisma Kapoor
Karisma Kapoor is an acclaimed Indian film actress best known for her leading roles in popular Hindi movies of the 1990s and early 2000s.
-
C.
Kareena Kapoor Khan
Kareena Kapoor Khan is a prominent Indian film actress known for her versatile roles in Bollywood and her influential presence in contemporary Hindi cinema.
-
D.
Neha Kapur
Neha Kapur is an Indian model, former Miss India Universe 2006, and fashion entrepreneur.
-
E.
Deepika Padukone
Deepika Padukone is a leading Indian film actress and producer, internationally recognized for her work in Bollywood and Hollywood as well as her advocacy for mental health awareness.
- 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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9485dd88190bc2cf2adf39d48ee |
completed | March 31, 2026, 3:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea871dd3081908e24c4d1c60a8381 |
completed | April 2, 2026, 5:33 p.m. |
| NEDg | Description generation | batch_69cea996a5c48190a12ffe8e282d2d9c |
completed | April 2, 2026, 5:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ceadb2d52c8190aada1d797753663e |
completed | April 2, 2026, 5:56 p.m. |
Created at: March 30, 2026, 6:20 p.m.