Triple
T18078501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Archer |
E432622
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jeffrey Archer |
—
|
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: Jeffrey Archer | Statement: [Mary Archer, spouse, Jeffrey Archer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Archer Context triple: [Mary Archer, spouse, Jeffrey Archer]
-
A.
Jeffrey Archer
chosen
Jeffrey Archer is a British author and former politician best known for his bestselling novels and thrillers.
-
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.
Frederick Forsyth
Frederick Forsyth is a British thriller writer renowned for his meticulously researched, politically charged novels such as "The Day of the Jackal."
-
D.
Reginald Hill
Reginald Hill was a British crime novelist best known for his long-running Dalziel and Pascoe detective series.
-
E.
Winston Graham
Winston Graham was a British novelist best known for writing the historical Poldark series set in 18th-century Cornwall.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f6a85481909894c39c8be98d5d |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:27 a.m.