Triple
T10803759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basu |
E254908
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Sanjib Basu
Sanjib Basu is a statistician known for his contributions to Bayesian methods and statistical theory.
|
E891529
|
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: Sanjib Basu | Statement: [Basu, hasNotableBearer, Sanjib Basu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanjib Basu Context triple: [Basu, hasNotableBearer, Sanjib Basu]
-
A.
Sanjib Bose
Sanjib Bose is an individual notable for bearing the surname Bose, associated with the broader Bose family name.
-
B.
Sanjib Bhattacharyya
Sanjib Bhattacharyya is an economist and academic recognized as a notable scholar associated with the Delhi School of Economics.
-
C.
Bijon Bhattacharya
Bijon Bhattacharya was a prominent Indian playwright and actor associated with the Indian People's Theatre Association and known for his socially conscious Bengali dramas.
-
D.
Hemanta Mukhopadhyay
Hemanta Mukhopadhyay was a legendary Indian playback singer and music director, especially renowned for his work in Bengali and Hindi cinema and his contributions to Rabindra Sangeet.
-
E.
Parag Das
Parag Das is a former Indian cricketer best known for representing Assam as a top-order batsman in domestic cricket.
- 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: Sanjib Basu Triple: [Basu, hasNotableBearer, Sanjib Basu]
Generated description
Sanjib Basu is a statistician known for his contributions to Bayesian methods and statistical theory.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sanjib Basu Target entity description: Sanjib Basu is a statistician known for his contributions to Bayesian methods and statistical theory.
-
A.
Sanjib Bose
Sanjib Bose is an individual notable for bearing the surname Bose, associated with the broader Bose family name.
-
B.
Sanjib Bhattacharyya
Sanjib Bhattacharyya is an economist and academic recognized as a notable scholar associated with the Delhi School of Economics.
-
C.
Bijon Bhattacharya
Bijon Bhattacharya was a prominent Indian playwright and actor associated with the Indian People's Theatre Association and known for his socially conscious Bengali dramas.
-
D.
Hemanta Mukhopadhyay
Hemanta Mukhopadhyay was a legendary Indian playback singer and music director, especially renowned for his work in Bengali and Hindi cinema and his contributions to Rabindra Sangeet.
-
E.
Parag Das
Parag Das is a former Indian cricketer best known for representing Assam as a top-order batsman in domestic cricket.
- 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_69e15499158481908391f411420b19fc |
completed | April 16, 2026, 9:28 p.m. |
| NEDg | Description generation | batch_69e170cbbef081909d422d87b670ea3e |
completed | April 16, 2026, 11:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e1716689ac8190a2408af781003e77 |
completed | April 16, 2026, 11:31 p.m. |
Created at: April 8, 2026, 9:18 p.m.