Triple
T22760579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Robe |
E562975
|
entity |
| Predicate | authorOfSourceWork |
P2353
|
FINISHED |
| Object | Brian Moore |
—
|
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: Brian Moore | Statement: [Black Robe, authorOfSourceWork, Brian Moore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Moore Context triple: [Black Robe, authorOfSourceWork, Brian Moore]
-
A.
Brian Moore
chosen
Brian Moore was a Northern Irish-Canadian novelist and screenwriter known for his psychologically rich fiction and acclaimed film adaptations.
-
B.
Bryan Moore
Bryan Moore is a television writer and producer best known for co-creating the Disney XD science-fiction comedy series "Lab Rats."
-
C.
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.
-
D.
John Creasey
John Creasey was a prolific British crime and thriller novelist who wrote hundreds of books under numerous pseudonyms and became one of the most widely published authors of the 20th century.
-
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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a7c45b881908b29ba1439038789 |
completed | April 29, 2026, 3:26 a.m. |
Created at: April 17, 2026, 3:26 p.m.