Triple
T7455202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ness Wadia |
E172104
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object | Nusli Wadia |
E168080
|
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: Nusli Wadia | Statement: [Ness Wadia, parent, Nusli Wadia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nusli Wadia Context triple: [Ness Wadia, parent, Nusli Wadia]
-
A.
Nusli Wadia
chosen
Nusli Wadia is an Indian industrialist and chairman of the Wadia Group, known for leading major companies such as Bombay Dyeing and Britannia Industries.
-
B.
Praful Patel
Praful Patel is an Indian politician and former Union Minister, best known for his long association with Sharad Pawar and his influential role in national and Maharashtra politics.
-
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.
Neera Tanden
Neera Tanden is an American political consultant and policy expert who has held senior roles in Democratic administrations and think tanks, focusing on domestic and economic policy.
-
E.
Supriya Jolly Jindal
Supriya Jolly Jindal is an American philanthropist and former First Lady of Louisiana, known for her work in education and children's 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_69c68a66554c8190add75c65942c0317 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3af58dc819093fb0482482779a3 |
completed | March 27, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c834597d94819081f57de7d5ae30af |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:15 p.m.