Triple
T14363256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daisy Sudeikis |
E356156
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Daisy Sudeikis |
E356156
|
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: Daisy Sudeikis | Statement: [Daisy Sudeikis, name, Daisy Sudeikis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daisy Sudeikis Context triple: [Daisy Sudeikis, name, Daisy Sudeikis]
-
A.
Daisy Sudeikis
chosen
Daisy Sudeikis is the daughter of American actor and comedian Jason Sudeikis.
-
B.
Ellie Kemper
Ellie Kemper is an American actress and comedian best known for her roles in the sitcoms "The Office" and "Unbreakable Kimmy Schmidt."
-
C.
Rachel Van Dyken
Rachel Van Dyken is a contemporary American author best known for her popular romance novels and New York Times bestselling series.
-
D.
Alison Brie
Alison Brie is an American actress known for her roles in television series like "Community" and "Mad Men," as well as her voice work in animated films.
-
E.
Aidy Bryant
Aidy Bryant is an American actress and comedian best known for her work on "Saturday Night Live" and the Hulu series "Shrill."
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8fabec088190bd8128371b29e958 |
completed | April 14, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd550ca6b88190b76cd486bdd66fdf |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:15 a.m.