Triple
T17546743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel |
E427344
|
entity |
| Predicate | workAuthor |
P4244
|
FINISHED |
| Object | Frederick Forsyth |
—
|
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: Frederick Forsyth | Statement: [Michel, workAuthor, Frederick Forsyth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frederick Forsyth Context triple: [Michel, workAuthor, Frederick Forsyth]
-
A.
Frederick Forsyth
chosen
Frederick Forsyth is a British thriller writer renowned for his meticulously researched, politically charged novels such as "The Day of the Jackal."
-
B.
Len Deighton
Len Deighton is a British author and historian best known for his spy novels, including "The IPCRESS File," and his influential works on military history.
-
C.
Robert Ludlum
Robert Ludlum was an American author best known for his fast-paced espionage and thriller novels, including the Jason Bourne series.
-
D.
Nelson DeMille
Nelson DeMille is an American novelist best known for his suspenseful thrillers and crime novels featuring complex plots, military and law-enforcement settings, and sharp, witty dialogue.
-
E.
Jeffrey Archer
Jeffrey Archer is a British author and former politician best known for his bestselling novels and thrillers.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e454626cfc8190a2602ba4934b8e6d |
completed | April 19, 2026, 4:04 a.m. |
Created at: April 10, 2026, 5:49 a.m.