Triple
T19738590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Rydell |
E474052
|
entity |
| Predicate | romanticInterestIn |
P7325
|
FINISHED |
| Object | Rebecca Wells |
—
|
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: Rebecca Wells | Statement: [Dan Rydell, romanticInterestIn, Rebecca Wells]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rebecca Wells Context triple: [Dan Rydell, romanticInterestIn, Rebecca Wells]
-
A.
Rebecca Wells
chosen
Rebecca Wells is an American author best known for her bestselling novel "Divine Secrets of the Ya-Ya Sisterhood" and its related works exploring Southern women’s lives and friendships.
-
B.
Cathryn Michon
Cathryn Michon is an American screenwriter, author, and filmmaker known for adapting bestselling novels such as "A Dog’s Journey" for the screen.
-
C.
Francine Rivers
Francine Rivers is a bestselling American author known for her inspirational Christian fiction novels, particularly "Redeeming Love."
-
D.
Sara Gruen
Sara Gruen is a Canadian-American novelist best known for her bestselling historical novel "Water for Elephants."
-
E.
Margot Winspear
Margot Winspear was a philanthropist known for her support of the arts, particularly through major contributions to cultural institutions in Dallas, Texas.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6515f6efc8190a3da113847464399 |
completed | April 20, 2026, 4:16 p.m. |
Created at: April 10, 2026, 1:47 p.m.