Triple
T20030676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelley Foreshore |
E495113
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Shelley |
—
|
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: Shelley | Statement: [Shelley Foreshore, locatedIn, Shelley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shelley Context triple: [Shelley Foreshore, locatedIn, Shelley]
-
A.
Shelley
Shelley is the surname of Mary Shelley, the English novelist best known as the author of the Gothic classic "Frankenstein."
-
B.
Shelley
Shelley is a village in West Yorkshire, England, known for its rural setting and proximity to other small communities like Skelmanthorpe.
-
C.
Shelley
"Shelley" is a British television sitcom best known for its portrayal of an underemployed, sardonic intellectual navigating life and work in late 20th-century England.
-
D.
Shelley
Shelley is a key supporting character in the psychological thriller film "Don't Worry Darling," portrayed as the elegant yet enigmatic wife of the community's leader.
-
E.
Shelley
chosen
Shelley is a small village in Suffolk, England, situated within the scenic Dedham Vale countryside.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66291a00c8190b0b895909f32d623 |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:36 p.m.