Triple
T20469662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudy Baylor |
E502153
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | John Grisham |
—
|
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: John Grisham | Statement: [Rudy Baylor, createdBy, John Grisham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Grisham Context triple: [Rudy Baylor, createdBy, John Grisham]
-
A.
John Grisham
chosen
John Grisham is a bestselling American author renowned for his legal thrillers, many of which have been adapted into successful films.
-
B.
Scott Turow
Scott Turow is an American novelist and lawyer best known for his bestselling legal thrillers that helped popularize the modern courtroom drama genre.
-
C.
Ty Grisham
Ty Grisham is a child of bestselling American legal-thriller author John Grisham.
-
D.
Charles Portis
Charles Portis was an American novelist best known for his deadpan comic style and for writing the Western novel "True Grit," which inspired multiple film adaptations.
-
E.
David Baldacci
David Baldacci is a bestselling American novelist known for his fast-paced legal and political thrillers, including "Absolute Power" and the "King & Maxwell" series.
- 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6995f753081909bbe03f7c251d9c1 |
completed | April 20, 2026, 9:23 p.m. |
Created at: April 16, 2026, 11:33 a.m.