Triple
T21990564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadie Jones |
E543072
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object | Sadie Jones |
—
|
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: Sadie Jones | Statement: [Sadie Jones, hasName, Sadie Jones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sadie Jones Context triple: [Sadie Jones, hasName, Sadie Jones]
-
A.
Sadie Jones
chosen
Sadie Jones is a British novelist best known for her award-winning debut novel "The Outcast" and subsequent works exploring family, trauma, and social constraint.
-
B.
Sadie Jones
Sadie Jones is a central comedic character in the romantic comedy film "License to Wed," known for her involvement in the chaotic premarital counseling that drives the story’s humor and conflict.
-
C.
Jessie Burton
Jessie Burton is a British novelist best known for her bestselling historical fiction debut "The Miniaturist."
-
D.
Jennifer Haigh
Jennifer Haigh is an American novelist and short story writer known for her character-driven literary fiction exploring family, class, and the impact of the energy industry on small-town life.
-
E.
Beth Winters
Beth Winters is a fictional character from the 2012 ensemble drama-comedy film "Darling Companion."
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270d7cbc819086eea86be04a2ec0 |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:05 p.m.