Triple
T12324898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sal Khan |
E293803
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Umaima Marvi |
E293803
|
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: Umaima Marvi | Statement: [Sal Khan, spouse, Umaima Marvi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umaima Marvi Context triple: [Sal Khan, spouse, Umaima Marvi]
-
A.
Umaima Marvi
chosen
Umaima Marvi is the wife of educator and Khan Academy founder Sal Khan.
-
B.
Lateef Fatima Khan
Lateef Fatima Khan was the mother of Bollywood superstar Shah Rukh Khan and came from a respected Muslim family with a background in social service and activism.
-
C.
Hina Jilani
Hina Jilani is a prominent Pakistani lawyer and human rights activist known for her pioneering work in women's rights, civil liberties, and international justice.
-
D.
Nasira Iqbal
Nasira Iqbal is a Pakistani jurist and former judge of the Lahore High Court, recognized as one of the country’s prominent female legal figures.
-
E.
Fara Sherazi
Fara Sherazi is a fictional CIA analyst character from the television series "Homeland," portrayed by actress Nazanin Boniadi.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4e7e588190b37e2413bc649198 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6346a3f34819091882004ab558347 |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:53 p.m.