Triple
T11591719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stewart Resnick |
E274897
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Lynda Resnick |
E248729
|
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: Lynda Resnick | Statement: [Stewart Resnick, spouse, Lynda Resnick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lynda Resnick Context triple: [Stewart Resnick, spouse, Lynda Resnick]
-
A.
Lynda Resnick
chosen
Lynda Resnick is an American billionaire businesswoman and philanthropist known for co-owning The Wonderful Company and for her extensive arts and cultural patronage.
-
B.
Lynda Bernhard
Lynda Bernhard is known as the wife of American film producer Harvey Bernhard.
-
C.
Lynda Dryden
Lynda Dryden is the wife of former NHL goaltender and Canadian politician Ken Dryden.
-
D.
Rachel Resnick
Rachel Resnick is an American author and memoirist known for her candid, often humorous explorations of personal relationships and emotional vulnerability.
-
E.
Laura Rister
Laura Rister is a film producer and executive known for her work on independent and prestige projects, including the financial thriller "Margin Call."
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d894643ae48190837502b713f5b9c6 |
completed | April 10, 2026, 6:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef8269c4f48190aaf238a64c5caf1d |
completed | April 27, 2026, 3:36 p.m. |
Created at: April 8, 2026, 9:38 p.m.