Triple
T16524211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Follett |
E401392
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Follett |
E401392
|
NE FINISHED |
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: Follett | Statement: [Ken Follett, familyName, Follett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Follett Context triple: [Ken Follett, familyName, Follett]
-
A.
Follett
chosen
Follett is a surname most prominently associated with British author Ken Follett, known for his bestselling historical and thriller novels.
-
B.
Faulks
Faulks is the surname of British novelist and journalist Sebastian Faulks, best known for his historical and literary fiction.
-
C.
Rinehart
Rinehart is a small unincorporated community located in the U.S. state of Missouri.
-
D.
Brenan
Brenan is a given name and surname that serves as a spelling variant of Brennen.
-
E.
Figes
Figes is a surname most notably associated with British historian and author Orlando Figes, known for his works on Russian and European history.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed2622c8190b6429a49ca92284a |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00608b7f6081909912dd575979f8d7 |
completed | May 10, 2026, 10:40 a.m. |
Created at: April 10, 2026, 5:14 a.m.