Triple
T15546966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Spitz |
E370633
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Suzy Weiner |
—
|
NE NERFINISHED |
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: Suzy Weiner | Statement: [Mark Spitz, spouse, Suzy Weiner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suzy Weiner Context triple: [Mark Spitz, spouse, Suzy Weiner]
-
A.
Suzy Weiner
chosen
Suzy Weiner is best known as the wife of legendary American Olympic swimmer Mark Spitz.
-
B.
Sue Snyder
Sue Snyder is an American public figure and advocate best known as the wife of former Michigan Governor Rick Snyder and for her involvement in charitable and civic initiatives in the state.
-
C.
Susan Weiler
Susan Weiler is a prominent landscape architect and design leader known for her influential work with the firm OLIN on major public and urban spaces.
-
D.
Shari Weiser
Shari Weiser is a puppeteer and performer best known for physically portraying the character Hoggle in Jim Henson’s fantasy film "Labyrinth."
-
E.
Suzanne Diller
Suzanne Diller is the daughter of pioneering American stand-up comedian and actress Phyllis Diller.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a9073948190b6e9cf504aacc7cf |
completed | April 16, 2026, 2:33 a.m. |
Created at: April 10, 2026, 4:08 a.m.