Triple
T19191413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anant Ambani |
E469847
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Nita Ambani |
—
|
NE NERFINISHED |
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: Nita Ambani | Statement: [Anant Ambani, mother, Nita Ambani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nita Ambani Context triple: [Anant Ambani, mother, Nita Ambani]
-
A.
Nita Ambani
chosen
Nita Ambani is an Indian philanthropist and businesswoman, known for her leadership roles in Reliance Industries’ ventures and for founding the Reliance Foundation.
-
B.
Isha Ambani
Isha Ambani is an Indian businesswoman and heiress who serves as a leader in Reliance Industries’ retail and digital ventures.
-
C.
Tina Ambani
Tina Ambani is an Indian former Bollywood actress and prominent philanthropist who chairs the Kokilaben Dhirubhai Ambani Hospital and leads several arts and elder-care initiatives.
-
D.
Kokilaben Ambani
Kokilaben Ambani is an Indian philanthropist and matriarch of the Ambani family, known as the widow of industrialist Dhirubhai Ambani and mother of business magnate Mukesh Ambani.
-
E.
Ambani
Ambani is a prominent Indian business family best known for its vast industrial conglomerates and immense influence on the country’s corporate and economic landscape.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f8a226dc8190a8a96960a4180298 |
completed | April 20, 2026, 9:57 a.m. |
Created at: April 10, 2026, 12:07 p.m.