Triple
T19128104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How to Make an American Quilt |
E468238
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Sarah Pillsbury |
—
|
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: Sarah Pillsbury | Statement: [How to Make an American Quilt, producer, Sarah Pillsbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Pillsbury Context triple: [How to Make an American Quilt, producer, Sarah Pillsbury]
-
A.
Sarah Pillsbury
chosen
Sarah Pillsbury is an American film producer best known for her work on acclaimed independent films, including the 1992 drama "Love Field."
-
B.
Michelle Rounds
Michelle Rounds was an American executive and LGBTQ+ advocate best known for her former marriage to comedian and television personality Rosie O'Donnell.
-
C.
Erinn Bartlett
Erinn Bartlett is an American actress and former beauty pageant titleholder known for supporting roles in film and television.
-
D.
Elizabeth Claire Kemper
Elizabeth Claire Kemper is an American actress and comedian best known for her roles on the TV series "The Office" and "Unbreakable Kimmy Schmidt."
-
E.
Grace Briggs
Grace Briggs is the warm-hearted waitress and grieving widow who becomes the romantic lead opposite a heart-transplant recipient in the film "Return to Me."
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3ceb5808190b3b53d9e8df3605a |
completed | April 20, 2026, 8:29 a.m. |
Created at: April 10, 2026, 12:05 p.m.