Triple
T23507624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lee Wiley |
E572326
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jess Stacy |
—
|
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: Jess Stacy | Statement: [Lee Wiley, spouse, Jess Stacy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jess Stacy Context triple: [Lee Wiley, spouse, Jess Stacy]
-
A.
Jess Stacy
chosen
Jess Stacy was an American jazz pianist best known for his work with Benny Goodman’s orchestra and his celebrated solo on “Sing, Sing, Sing.”
-
B.
Michelle Stacy
Michelle Stacy is an American former child voice actress best known for her roles in animated films of the 1970s and early 1980s.
-
C.
Stacey Fountain
Stacey Fountain is known for being one of the former wives of American rock musician Gregg Allman.
-
D.
Stacy McKee
Stacy McKee is an American television writer and producer best known for her long-running work on "Grey's Anatomy" and for creating its firefighter-focused spin-off series.
-
E.
Stacy Barrett
Stacy Barrett is a bubbly, loyal, and somewhat ditzy best friend character from the legal comedy-drama TV series "Drop Dead Diva."
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a901c9908190a781e79fe8b96743 |
completed | April 29, 2026, 6:45 a.m. |
Created at: April 17, 2026, 6:07 p.m.