Triple
T20015055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivo per lei |
E494694
|
entity |
| Predicate | notablePerformer |
P17435
|
FINISHED |
| Object | Judy Weiss |
—
|
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: Judy Weiss | Statement: [Vivo per lei, notablePerformer, Judy Weiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Judy Weiss Context triple: [Vivo per lei, notablePerformer, Judy Weiss]
-
A.
Judy Weiss
chosen
Judy Weiss is a German singer best known for her pop and musical theatre performances, including duet collaborations with international artists.
-
B.
Judy Levitt
Judy Levitt is an American actress best known for her long marriage to Star Trek actor Walter Koenig and for appearing in several of his film and television projects.
-
C.
Julie Weiss
Julie Weiss is an acclaimed American costume designer known for her work in film, television, and theater, including multiple Academy Award–nominated productions.
-
D.
Judie Aronson
Judie Aronson is an American actress best known for her roles in 1980s films and television, including a notable appearance in the horror genre.
-
E.
Janet Margolin
Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623bba1881908440c92f08729ec1 |
completed | April 20, 2026, 5:28 p.m. |
Created at: April 11, 2026, 3:34 p.m.