Triple
T8010455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burgh Heath |
E186474
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Banstead |
E29183
|
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: Banstead | Statement: [Burgh Heath, near, Banstead]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Banstead Context triple: [Burgh Heath, near, Banstead]
-
A.
Banstead
chosen
Banstead is a suburban town in southeast England known for its village-like high street and green spaces within the county of Surrey.
-
B.
Beckenham
Beckenham is a suburban town in southeast London known for its residential character, green spaces, and commuter links into central London.
-
C.
Oxted
Oxted is a commuter town in southeast England known for its proximity to London and location at the foot of the North Downs.
-
D.
Burgess Hill
Burgess Hill is a town in southeastern England known as a commuter hub with residential areas and light industry, situated within the county of West Sussex.
-
E.
Beddington
Beddington is a suburban area in South London known for its historic village core, green spaces, and proximity to Croydon and central London.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d70caf8819090a9f98025470c0d |
completed | March 31, 2026, 3:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bc96f7288190ab8d1bbf9d428903 |
completed | April 5, 2026, 1:36 a.m. |
Created at: March 30, 2026, 5:19 p.m.