Triple
T21991224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa Bayer |
E543093
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Vanessa Bayer |
—
|
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: Vanessa Bayer | Statement: [Vanessa Bayer, name, Vanessa Bayer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vanessa Bayer Context triple: [Vanessa Bayer, name, Vanessa Bayer]
-
A.
Vanessa Bayer
chosen
Vanessa Bayer is an American comedian and actress best known for her work as a cast member on "Saturday Night Live" and for her roles in various film and television comedies.
-
B.
Vanessa DiBernardo
Vanessa DiBernardo is an American professional soccer midfielder known for her playmaking ability in the National Women's Soccer League and her standout collegiate career at the University of Illinois.
-
C.
Vanessa Ferlito
Vanessa Ferlito is an American actress known for her roles in films like "Death Proof" and TV series such as "CSI: NY" and "NCIS: New Orleans."
-
D.
Vanessa Loring
Vanessa Loring is a key supporting character in the film "Juno," portrayed as a woman longing to adopt a child and struggling with the complexities of marriage and motherhood.
-
E.
Vanessa Roth
Vanessa Roth is an Academy Award-winning American documentary filmmaker known for her socially conscious films and work in education and social justice.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270d7cbc819086eea86be04a2ec0 |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:05 p.m.