Triple
T3110661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banga |
E64940
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Sanjiv Banga
Sanjiv Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
|
E328798
|
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: Sanjiv Banga | Statement: [Banga, hasNotableBearer, Sanjiv Banga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanjiv Banga Context triple: [Banga, hasNotableBearer, Sanjiv Banga]
-
A.
Sanjiv Singh
Sanjiv Singh is a robotics researcher and professor known for his work in autonomous systems and field robotics at Carnegie Mellon University.
-
B.
Sanjay Banerji
Sanjay Banerji is an economist and academic recognized for his scholarly contributions associated with the Delhi School of Economics.
-
C.
Sanjay Jain
Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
-
D.
Ravi Bhalla
Ravi Bhalla is an American attorney and politician who became the first Sikh mayor of Hoboken, New Jersey, and one of the first turbaned Sikh mayors in the United States.
-
E.
Kumar Patel
Kumar Patel is a laid-back, marijuana-loving Korean American character from the "Harold & Kumar" comedy film series, known for his misadventurous escapades with his best friend Harold Lee.
- 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: Sanjiv Banga Triple: [Banga, hasNotableBearer, Sanjiv Banga]
Generated description
Sanjiv Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sanjiv Banga Target entity description: Sanjiv Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
-
A.
Sanjiv Singh
Sanjiv Singh is a robotics researcher and professor known for his work in autonomous systems and field robotics at Carnegie Mellon University.
-
B.
Sanjay Banerji
Sanjay Banerji is an economist and academic recognized for his scholarly contributions associated with the Delhi School of Economics.
-
C.
Sanjay Jain
Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
-
D.
Ravi Bhalla
Ravi Bhalla is an American attorney and politician who became the first Sikh mayor of Hoboken, New Jersey, and one of the first turbaned Sikh mayors in the United States.
-
E.
Kumar Patel
Kumar Patel is a laid-back, marijuana-loving Korean American character from the "Harold & Kumar" comedy film series, known for his misadventurous escapades with his best friend Harold Lee.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada43954f0819096a96331bf3c53a8 |
completed | March 8, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f5cfc7c8190b867794c0e9a271e |
completed | March 12, 2026, 12:57 a.m. |
| NEDg | Description generation | batch_69b2101824c0819097dc967d83d18751 |
completed | March 12, 2026, 1 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b210886d308190b120beb8f6bcbf3a |
completed | March 12, 2026, 1:02 a.m. |
Created at: March 8, 2026, 3:04 p.m.