Triple
T19293407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilton House estate |
E482496
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Salisbury |
—
|
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: Salisbury | Statement: [Wilton House estate, near, Salisbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salisbury Context triple: [Wilton House estate, near, Salisbury]
-
A.
Salisbury
Salisbury is the former colonial-era name of Zimbabwe’s capital city, now known as Harare.
-
B.
Salisbury
Salisbury is a small Canadian village in southeastern New Brunswick known as a local service and residential community along the Petitcodiac River.
-
C.
Salisbury
Salisbury is a suburban city in the northern part of the Adelaide metropolitan area in South Australia, serving as a key residential and industrial hub.
-
D.
Salisbury
Salisbury is a village on the west coast of Dominica known for its fishing community and proximity to scenic Caribbean beaches.
-
E.
Salisbury
chosen
Salisbury is a historic cathedral city in Wiltshire, England, renowned for its medieval architecture and proximity to the ancient monument of Stonehenge.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc824b448190865230eed8ef9ebf |
completed | April 20, 2026, 10:14 a.m. |
Created at: April 10, 2026, 1:31 p.m.