Triple
T12946372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manvinder Singh Banga |
E309776
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Ajay Banga |
E10452
|
NE FINISHED |
How this triple was built (2 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: Ajay Banga | Statement: [Manvinder Singh Banga, relative, Ajay Banga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ajay Banga Context triple: [Manvinder Singh Banga, relative, Ajay Banga]
-
A.
Ajay Banga
chosen
Ajay Banga is an Indian-American business executive and former Mastercard CEO who became president of the World Bank, focusing on global development and climate-related challenges.
-
B.
Sanjiv Banga
Sanjiv Banga is an individual notable enough to be recognized as a prominent bearer of the surname Banga.
-
C.
Vikram Pandit
Vikram Pandit is an Indian-American banker best known for serving as the CEO of Citigroup during the global financial crisis.
-
D.
Nusli Wadia
Nusli Wadia is an Indian industrialist and chairman of the Wadia Group, known for leading major companies such as Bombay Dyeing and Britannia Industries.
-
E.
Navin Chowdhry
Navin Chowdhry is a British actor known for his work in television, film, and theatre, including prominent roles in UK comedy and drama series.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e1b3694819098527dcea3cfed93 |
completed | April 10, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8d9669c819090471eb7e035d83d |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 9, 2026, 5:43 p.m.