Triple
T23063217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norah Silverberg |
E574960
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Rachel Cohn |
—
|
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: Rachel Cohn | Statement: [Norah Silverberg, createdBy, Rachel Cohn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachel Cohn Context triple: [Norah Silverberg, createdBy, Rachel Cohn]
-
A.
Rachel Cohn
chosen
Rachel Cohn is an American young adult novelist best known for co-authoring popular books like "Nick and Norah's Infinite Playlist," which have been adapted into successful films.
-
B.
Andrea Sachs
Andrea Sachs is the ambitious young journalist who becomes the overworked assistant to powerful fashion editor Miranda Priestly in "The Devil Wears Prada."
-
C.
Dawn Barlett
Dawn Barlett is the central protagonist of the British television series "My Generation," around whose life and experiences the story revolves.
-
D.
Natasha Bassett
Natasha Bassett is an Australian actress and screenwriter known for roles in film and television, including biographical and dramatic projects.
-
E.
Risa Gertner
Risa Gertner is a film producer known for her work on the romantic comedy "The First Time."
- 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_69e245bd6e4c8190bb8942245b68cad5 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f189a1f49c81909db7e0473ec2bb1b |
completed | April 29, 2026, 4:31 a.m. |
Created at: April 17, 2026, 3:55 p.m.