Triple
T22846678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bappi Lahiri |
E566238
|
entity |
| Predicate | parents |
P7318
|
FINISHED |
| Object |
Bansari Lahiri
Bansari Lahiri is the mother of renowned Indian music composer and singer Bappi Lahiri.
|
E1556629
|
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: Bansari Lahiri | Statement: [Bappi Lahiri, parents, Bansari Lahiri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bansari Lahiri Context triple: [Bappi Lahiri, parents, Bansari Lahiri]
-
A.
Tapati Lahiri
Tapati Lahiri is the mother of acclaimed author Jhumpa Lahiri and a key figure in the writer’s Bengali-Indian family background.
-
B.
Sujata Basu
Sujata Basu is a notable individual associated with the surname Basu, recognized as a distinguished bearer of that name.
-
C.
Jhumpa Lahiri
Jhumpa Lahiri is a Pulitzer Prize–winning author known for her nuanced portrayals of the Indian-American immigrant experience and themes of identity, displacement, and cultural conflict.
-
D.
Tanuja Chandra
Tanuja Chandra is an Indian film director and screenwriter known for her work in Hindi cinema, often focusing on strong female protagonists and socially relevant themes.
-
E.
Ronobir Lahiri
Ronobir Lahiri is a voice actor known for his work in the animated film "Elemental."
- 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: Bansari Lahiri Triple: [Bappi Lahiri, parents, Bansari Lahiri]
Generated description
Bansari Lahiri is the mother of renowned Indian music composer and singer Bappi Lahiri.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bansari Lahiri Target entity description: Bansari Lahiri is the mother of renowned Indian music composer and singer Bappi Lahiri.
-
A.
Tapati Lahiri
Tapati Lahiri is the mother of acclaimed author Jhumpa Lahiri and a key figure in the writer’s Bengali-Indian family background.
-
B.
Sujata Basu
Sujata Basu is a notable individual associated with the surname Basu, recognized as a distinguished bearer of that name.
-
C.
Jhumpa Lahiri
Jhumpa Lahiri is a Pulitzer Prize–winning author known for her nuanced portrayals of the Indian-American immigrant experience and themes of identity, displacement, and cultural conflict.
-
D.
Tanuja Chandra
Tanuja Chandra is an Indian film director and screenwriter known for her work in Hindi cinema, often focusing on strong female protagonists and socially relevant themes.
-
E.
Ronobir Lahiri
Ronobir Lahiri is a voice actor known for his work in the animated film "Elemental."
- 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_69e2458750b481908a8e4cf4609cc6cf |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e88fb408190a58c91486ea65169 |
completed | April 29, 2026, 3:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ba7b9d5888190a3c94d87904a24e2 |
completed | May 18, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_6a0ba8bb77bc81909c5422f9d73c1e70 |
completed | May 19, 2026, 12:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ba94752c48190a8892cac5ef862b2 |
completed | May 19, 2026, 12:05 a.m. |
Created at: April 17, 2026, 3:36 p.m.