Triple
T6596836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satya Nadella |
E148496
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Anupama Nadella |
E148496
|
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: Anupama Nadella | Statement: [Satya Nadella, spouse, Anupama Nadella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anupama Nadella Context triple: [Satya Nadella, spouse, Anupama Nadella]
-
A.
Anupama Nadella
chosen
Anupama Nadella is the wife of Microsoft CEO Satya Nadella and is known for her advocacy related to children with special needs, inspired by her own family experiences.
-
B.
Satya Nadella
Satya Nadella is an Indian-American business executive who serves as the CEO and chairman of Microsoft, known for steering the company’s transformation toward cloud computing and AI.
-
C.
Anjali Pichai
Anjali Pichai is an Indian-born chemical engineer and businesswoman best known as the wife of Google and Alphabet CEO Sundar Pichai.
-
D.
Indra Nooyi
Indra Nooyi is an Indian-American business executive best known for serving as the influential former CEO and chairperson of PepsiCo.
-
E.
Vas Narasimhan
Vas Narasimhan is an American physician-executive known for leading major strategic and innovation-driven transformations in the global pharmaceutical industry.
- 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_69c687e7b8688190811ffee72e096468 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aeecdd4c819092b87f4c91883154 |
completed | March 27, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eedfe3a88190a1d7fda9ff0dc9bd |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 1:56 p.m.