Triple
T18877701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badgers Mount |
E461730
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Knockholt |
—
|
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: Knockholt | Statement: [Badgers Mount, near, Knockholt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knockholt Context triple: [Badgers Mount, near, Knockholt]
-
A.
Knockholt
chosen
Knockholt is a rural village in the London Borough of Bromley, England, known for its countryside setting on the edge of Greater London and Kent.
-
B.
Paddock Wood
Paddock Wood is a small town in Kent, England, known for its agricultural history and role as a local transport and commercial hub.
-
C.
Hawkinge
Hawkinge is a village and civil parish in Kent, England, known for its historical association with World War II airfields and its location near Folkestone.
-
D.
Tangmere
Tangmere is a village in West Sussex, England, best known for its historic RAF airfield and aviation museum.
-
E.
Tidworth
Tidworth is a small garrison town in Wiltshire, England, known for its close association with the British Army and surrounding military installations.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3cfc4408190a7ae91459f75be52 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 10, 2026, 11:57 a.m.