Triple
T1392156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salman Rushdie |
E29982
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Padma Lakshmi |
E29992
|
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: Padma Lakshmi | Statement: [Salman Rushdie, spouse, Padma Lakshmi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Padma Lakshmi Context triple: [Salman Rushdie, spouse, Padma Lakshmi]
-
A.
Padma Lakshmi
chosen
Padma Lakshmi is an Indian-American author, model, and television host best known for hosting the cooking competition show "Top Chef."
-
B.
Sandra Lee
Sandra Lee is an American television chef and author known for her "Semi-Homemade" cooking concept and numerous Food Network shows.
-
C.
Anita Bose Pfaff
Anita Bose Pfaff is a German economist and academic, best known as the daughter of Indian independence leader Subhas Chandra Bose.
-
D.
Ashley Curry
Ashley Curry is an American local government official serving as the mayor of Vestavia Hills, Alabama.
-
E.
Rachel Ray
"Rachel Ray" is a 19th-century novel by Anthony Trollope that explores themes of love, religious influence, and social pressure in a small English town.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c360a7f08190ab7e903764b06fdf |
completed | March 1, 2026, 10:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acde28dd888190baa4a26f96f33e0a |
completed | March 8, 2026, 2:25 a.m. |
Created at: March 1, 2026, 7:59 p.m.