Triple
T4650488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smallfield |
E102281
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Horley |
E18812
|
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: Horley | Statement: [Smallfield, near, Horley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Horley Context triple: [Smallfield, near, Horley]
-
A.
Horley
chosen
Horley is a town in southeast England situated near Gatwick Airport, known as a commuter hub between London and the Sussex coast.
-
B.
Wakefield
Wakefield is a historic cathedral city in West Yorkshire, Northern England, known for its medieval heritage and role as an administrative and commercial center in the region.
-
C.
Wakefield
Wakefield is a picturesque village in western Quebec, Canada, known for its historic covered bridge, arts community, and scenic setting along the Gatineau River.
-
D.
Wakefield
Wakefield is a suburban town in Middlesex County, Massachusetts, known for its commuter access to Boston and its scenic Lake Quannapowitt.
-
E.
Yorkton
Yorkton is a small city in southeastern Saskatchewan, Canada, known as a regional hub for agriculture and services.
- 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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6302078081909451589d39c7b28c |
completed | March 20, 2026, 3:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be1040dbdc8190b9ab7b0b58bca308 |
completed | March 21, 2026, 3:28 a.m. |
Created at: March 20, 2026, 1:14 p.m.