Triple
T19544751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Jakes |
E489013
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | John Jakes |
—
|
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: John Jakes | Statement: [John Jakes, name, John Jakes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Jakes Context triple: [John Jakes, name, John Jakes]
-
A.
John Jakes
chosen
John Jakes was an American author best known for his historical novels, particularly his popular Civil War and American history sagas.
-
B.
Timothy Vreeland
Timothy Vreeland is the son of legendary fashion editor and style icon Diana Vreeland.
-
C.
Kenneth A. Roberts
Kenneth A. Roberts was an American Democratic politician who served as a U.S. Representative from Alabama in the mid-20th century.
-
D.
Nathan Furst
Nathan Furst is an American composer best known for scoring films and television series, particularly in the action and adventure genres.
-
E.
Robert Zane
Robert Zane is a prominent, high-powered attorney in the television series "Suits" and the father of paralegal-turned-lawyer Rachel Zane.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63875cf40819088db7c7969be1e3d |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 10, 2026, 1:41 p.m.