Triple
T16524932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Follett |
E401409
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Adam Follett |
E401409
|
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: Adam Follett | Statement: [Ken Follett, child, Adam Follett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adam Follett Context triple: [Ken Follett, child, Adam Follett]
-
A.
Adam Follett
chosen
Adam Follett is one of the children of bestselling British novelist Ken Follett.
-
B.
David Fursdon
David Fursdon is a British public servant and landowner who serves as the ceremonial representative of the Crown in the county of Devon.
-
C.
David Worth
David Worth is an American cinematographer and film director best known for his work on action films, including collaborations with Clint Eastwood and Jean-Claude Van Damme.
-
D.
Andrew Greer
Andrew Greer is an American author and singer-songwriter known for his work in contemporary Christian music and faith-based writing.
-
E.
Dan Talbot
Dan Talbot was an influential American film distributor and exhibitor known for championing foreign and independent cinema in the United States.
- 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_69e32ed323c081908218460aa4ae3cf6 |
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.