Triple
T3084221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Marvelous Mrs. Maisel |
E64330
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Susie Myerson |
E213611
|
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: Susie Myerson | Statement: [The Marvelous Mrs. Maisel, character, Susie Myerson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susie Myerson Context triple: [The Marvelous Mrs. Maisel, character, Susie Myerson]
-
A.
Susie Myerson
chosen
Susie Myerson is a tough, sharp-tongued talent manager and key supporting character on the television series "The Marvelous Mrs. Maisel."
-
B.
Suzanne Zimmer
Suzanne Zimmer is the wife of renowned film composer Hans Zimmer and the mother of several of his children.
-
C.
Suzanne Mulkern
Suzanne Mulkern is known for being the first wife of Apple co-founder Steve Wozniak.
-
D.
Beth Shuey
Beth Shuey is the former wife of NFL head coach Sean Payton and the mother of their two children.
-
E.
Sue Bayliss
Sue Bayliss is a supporting character in Arthur Miller’s play "All My Sons," depicted as a cynical, practical neighbor whose attitudes contrast with the idealism of other characters.
- 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_69ad857bb4c88190a4cf27893fcabed8 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada1e98a1c8190b1dd4a0a47f7d6c6 |
completed | March 8, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38ba897188190bf3ee24cb8a7384f |
completed | March 13, 2026, 3:59 a.m. |
Created at: March 8, 2026, 3:03 p.m.