Triple
T10803758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basu |
E254908
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Anindita Basu
Anindita Basu is an Indian technical writer and author known for her work in documentation and contributions to open knowledge resources.
|
E890831
|
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: Anindita Basu | Statement: [Basu, hasNotableBearer, Anindita Basu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anindita Basu Context triple: [Basu, hasNotableBearer, Anindita Basu]
-
A.
Sutapa Sikdar
Sutapa Sikdar is an Indian dialogue and screenplay writer best known as the wife of acclaimed actor Irrfan Khan.
-
B.
Sutapa Dasgupta
Sutapa Dasgupta is known as the wife of acclaimed Indian poet and National Award–winning filmmaker Buddhadeb Dasgupta.
-
C.
Kanika Banerjee
Kanika Banerjee was a renowned Indian Rabindra Sangeet vocalist celebrated for her emotive interpretations of Rabindranath Tagore’s songs.
-
D.
Swatilekha Chatterjee
Swatilekha Chatterjee was an acclaimed Indian stage and film actress best known for her powerful performance in Satyajit Ray’s classic film "Ghare Baire."
-
E.
Anuradha Banerjee
Anuradha Banerjee is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Banerjee.
- 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: Anindita Basu Triple: [Basu, hasNotableBearer, Anindita Basu]
Generated description
Anindita Basu is an Indian technical writer and author known for her work in documentation and contributions to open knowledge resources.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anindita Basu Target entity description: Anindita Basu is an Indian technical writer and author known for her work in documentation and contributions to open knowledge resources.
-
A.
Sutapa Sikdar
Sutapa Sikdar is an Indian dialogue and screenplay writer best known as the wife of acclaimed actor Irrfan Khan.
-
B.
Sutapa Dasgupta
Sutapa Dasgupta is known as the wife of acclaimed Indian poet and National Award–winning filmmaker Buddhadeb Dasgupta.
-
C.
Kanika Banerjee
Kanika Banerjee was a renowned Indian Rabindra Sangeet vocalist celebrated for her emotive interpretations of Rabindranath Tagore’s songs.
-
D.
Swatilekha Chatterjee
Swatilekha Chatterjee was an acclaimed Indian stage and film actress best known for her powerful performance in Satyajit Ray’s classic film "Ghare Baire."
-
E.
Anuradha Banerjee
Anuradha Banerjee is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Banerjee.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d73370e7388190885b104fc883456e |
completed | April 9, 2026, 5:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7c0907c8190b092bb6754fe4e52 |
completed | April 15, 2026, 8:40 p.m. |
| NEDg | Description generation | batch_69e0026e7900819087327db5f625169c |
completed | April 15, 2026, 9:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e0057a7704819096becb74dc261883 |
completed | April 15, 2026, 9:39 p.m. |
Created at: April 8, 2026, 9:18 p.m.