Triple
T2866330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ajaypal Singh Banga |
E63445
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Ritu Banga |
E63036
|
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: Ritu Banga | Statement: [Ajaypal Singh Banga, spouse, Ritu Banga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ritu Banga Context triple: [Ajaypal Singh Banga, spouse, Ritu Banga]
-
A.
Ritu Banga
chosen
Ritu Banga is an Indian-American businesswoman and co-founder of the talent advisory firm Zoomdojo, known also as the wife of Mastercard executive and World Bank president Ajay Banga.
-
B.
Jayati Ghosh
Jayati Ghosh is an Indian development economist known for her work on globalization, gender, and economic policy, and for her influential role in academic and policy debates on inequality and development.
-
C.
Madhabi Mukherjee
Madhabi Mukherjee is a renowned Indian actress best known for her powerful performances in classic Bengali films, particularly in collaboration with director Satyajit Ray.
-
D.
Labanya Das
Labanya Das was the wife of renowned Bengali poet Jibanananda Das and a figure associated with his personal and literary life.
-
E.
Ruma Bose
Ruma Bose is an entrepreneur, investor, and author known for her leadership roles in social impact ventures and global business initiatives.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfbb7ed4819096ca65391077e2af |
completed | March 7, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b08648923c8190bd544177b825a494 |
completed | March 10, 2026, 8:59 p.m. |
Created at: March 6, 2026, 10:02 p.m.