Triple
T4557493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloody Assizes |
E120514
|
entity |
| Predicate | hasLocation |
P40
|
FINISHED |
| Object | Devon |
E100074
|
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: Devon | Statement: [Bloody Assizes, hasLocation, Devon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Devon Context triple: [Bloody Assizes, hasLocation, Devon]
-
A.
Devon
chosen
Devon is a county in South West England known for its rugged coastlines, moorland national parks, and historic seaside towns.
-
B.
Devon
Devon is a residential neighbourhood located within the city of Fredericton in New Brunswick, Canada.
-
C.
Dorset
Dorset is a rural county on England’s south coast, known for its Jurassic Coast World Heritage Site, rolling countryside, and historic market towns.
-
D.
West Devon
West Devon is a largely rural local government district and borough in the county of Devon, England, known for its moorland landscapes and historic market towns.
-
E.
North Devon
North Devon is a largely rural district and coastal area in the county of Devon, England, known for its market towns, beaches, and scenic countryside.
- 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_69bd4636f1648190a701445c2fcd9c17 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd58163e6081909d5a3aae12c42a00 |
completed | March 20, 2026, 2:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69becf8f926481908f6e1cf33fc79a04 |
completed | March 21, 2026, 5:04 p.m. |
Created at: March 20, 2026, 1:09 p.m.