Triple
T13585663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marlesford |
E324551
|
entity |
| Predicate | civilParish |
P2739
|
FINISHED |
| Object | Marlesford |
E324551
|
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: Marlesford | Statement: [Marlesford, civilParish, Marlesford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marlesford Context triple: [Marlesford, civilParish, Marlesford]
-
A.
Marlesford
chosen
Marlesford is a small rural village and civil parish located in the English county of Suffolk.
-
B.
Belchford
Belchford is a small rural village in eastern England, situated within the scenic, rolling countryside of the Lincolnshire Wolds.
-
C.
Shillingford
Shillingford is a small village in South Oxfordshire, England, known for its rural setting near the River Thames and proximity to the town of Benson.
-
D.
Yarrowford
Yarrowford is a small village in the Scottish Borders region of Scotland, situated in the Yarrow Valley near the River Yarrow.
-
E.
Grindleford
Grindleford is a village in the Derbyshire Peak District of England, known for its scenic countryside, walking trails, and proximity to popular climbing and hiking areas.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb03310fc819092a56b9f2d73f560 |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bc148d08190821614a866d1a7f0 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.