Triple
T6691560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Crime Wave at Blandings |
E152638
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Sue Brown |
E230271
|
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: Sue Brown | Statement: [The Crime Wave at Blandings, featuresCharacter, Sue Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sue Brown Context triple: [The Crime Wave at Blandings, featuresCharacter, Sue Brown]
-
A.
Sue Brown
chosen
Sue Brown is a spirited and charming young woman in P. G. Wodehouse’s Blandings Castle stories, notably involved in romantic and comedic entanglements.
-
B.
Sue Wilkins
Sue Wilkins is a central character in Arthur C. Clarke’s science fiction novel "A Fall of Moondust," known for her role in the lunar tourism disaster that drives the story’s plot.
-
C.
Sue Johnston
Sue Johnston is an English actress best known for her roles in television dramas such as "Brookside," "The Royle Family," and "Waking the Dead."
-
D.
Suzanne Todd
Suzanne Todd is an American film producer known for her work on influential movies such as "Memento" and the "Austin Powers" series.
-
E.
Suzanne Surtees
Suzanne Surtees is the daughter of acclaimed American cinematographer Bruce Surtees.
- 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_69c6880687b08190805278b504d1c92c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6b15276208190b4c0e90ca337d2b4 |
completed | March 27, 2026, 4:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7581d4fb081908530cfd5f7bcba24 |
completed | March 28, 2026, 4:25 a.m. |
Created at: March 27, 2026, 2:05 p.m.