Triple
T8129624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yes Day |
E189821
|
entity |
| Predicate | basedOnAuthor |
P2806
|
FINISHED |
| Object | Amy Krouse Rosenthal |
E590986
|
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: Amy Krouse Rosenthal | Statement: [Yes Day, basedOnAuthor, Amy Krouse Rosenthal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amy Krouse Rosenthal Context triple: [Yes Day, basedOnAuthor, Amy Krouse Rosenthal]
-
A.
Amy Krouse Rosenthal
chosen
Amy Krouse Rosenthal was an American author, filmmaker, and radio host best known for her inventive children's books and poignant personal essays, including her widely read New York Times piece "You May Want to Marry My Husband."
-
B.
Lauren Munsch
Lauren Munsch is a film producer best known for her work on the coming-of-age drama "The Wackness."
-
C.
Emily Jenkins
Emily Jenkins is an American author best known for her children's books and young adult fiction, often written under the pen name E. Lockhart.
-
D.
Pamela Gray
Pamela Gray is an American screenwriter known for her work on character-driven drama films, including the military biographical film "Megan Leavey."
-
E.
Lane Smith
Lane Smith was an American character actor known for his roles in film and television, including portrayals of authoritative and often gruff figures.
- 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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb43b6b4dc8190be237e6dd21c863b |
completed | March 31, 2026, 3:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc947a7354819088c6f3cc6ab677cf |
completed | April 1, 2026, 3:43 a.m. |
Created at: March 30, 2026, 5:34 p.m.