Triple
T22230324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The River (novel) |
E549448
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Rumer Godden |
—
|
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: Rumer Godden | Statement: [The River (novel), author, Rumer Godden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rumer Godden Context triple: [The River (novel), author, Rumer Godden]
-
A.
Rumer Godden
chosen
Rumer Godden was a British author best known for her novels and stories often set in India, such as "Black Narcissus" and "The River," which explore complex emotional and spiritual themes.
-
B.
Lucille Findley
Lucille Findley was the wife of longtime U.S. Congressman and author Paul Findley.
-
C.
Jessica Burdett
Jessica Burdett is a television producer best known for her executive production work on the psychological thriller series "Behind Her Eyes."
-
D.
Wendelin Van Draanen
Wendelin Van Draanen is an American author best known for her young adult and children’s novels, including the popular book "Flipped."
-
E.
Susan Sawyer
Susan Sawyer is the daughter of American actress and designer Barbara Bel Geddes, known for her work on stage, film, and the television series "Dallas."
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf2a26c81908aaf614d7c75e219 |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:37 p.m.