Triple
T17632360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Divorce |
E430008
|
entity |
| Predicate | authorOfSourceWork |
P2353
|
FINISHED |
| Object | Diane Johnson |
—
|
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: Diane Johnson | Statement: [Le Divorce, authorOfSourceWork, Diane Johnson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diane Johnson Context triple: [Le Divorce, authorOfSourceWork, Diane Johnson]
-
A.
Diane Johnson
chosen
Diane Johnson is an American novelist and essayist best known for co-writing the screenplay for Stanley Kubrick’s film adaptation of Stephen King’s "The Shining."
-
B.
Diane Johnson
Diane Johnson is a sharp-witted, precocious youngest daughter known for her dark humor and deadpan personality on the TV sitcom "Black-ish."
-
C.
Sue Miller
Sue Miller is the wife of American musician Jeff Tweedy, frontman of the band Wilco.
-
D.
Joyce Harwood
Joyce Harwood is a central femme fatale-style figure in the 1946 film noir "The Blue Dahlia," entangled in a web of murder, deception, and romantic tension.
-
E.
Andrea Barrett
Andrea Barrett is an American novelist and short story writer best known for her historically rich, science-infused fiction, including the National Book Award–winning collection "Ship Fever."
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46dc276b48190923f1869ebfe4400 |
completed | April 19, 2026, 5:53 a.m. |
Created at: April 10, 2026, 5:52 a.m.