Triple
T11994358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain Jefferson Kyle Kidd |
E285489
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Paulette Jiles |
E285488
|
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: Paulette Jiles | Statement: [Captain Jefferson Kyle Kidd, creator, Paulette Jiles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paulette Jiles Context triple: [Captain Jefferson Kyle Kidd, creator, Paulette Jiles]
-
A.
Paulette Jiles
chosen
Paulette Jiles is an American poet and novelist best known for her historical fiction, including the novel "News of the World."
-
B.
Kathleen Kent
Kathleen Kent is an American novelist known for her historical fiction, particularly works exploring the Salem witch trials and early American history.
-
C.
Sara Gruen
Sara Gruen is a Canadian-American novelist best known for her bestselling historical novel "Water for Elephants."
-
D.
Francine Rivers
Francine Rivers is a bestselling American author known for her inspirational Christian fiction novels, particularly "Redeeming Love."
-
E.
Kristin Yancey
Kristin Yancey is a fictional character from the American television sitcom "Kristin."
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b211688190bfe6dd15c3f96d2f |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f47273e1088190b899071baff1375a |
completed | May 1, 2026, 9:29 a.m. |
Created at: April 8, 2026, 9:46 p.m.