Triple
T7326993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uttlesford |
E168899
|
entity |
| Predicate | hasElectoralWard |
P962
|
FINISHED |
| Object | Saffron Walden Audley |
E181168
|
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: Saffron Walden Audley | Statement: [Uttlesford, hasElectoralWard, Saffron Walden Audley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saffron Walden Audley Context triple: [Uttlesford, hasElectoralWard, Saffron Walden Audley]
-
A.
Saffron Walden
chosen
Saffron Walden is a historic market town in Essex, England, known for its well-preserved medieval architecture and former saffron trade.
-
B.
Bennetts End
Bennetts End is a residential area and suburb located within the county of Hertfordshire in England.
-
C.
Canewdon
Canewdon is a historic rural village in Essex, England, noted for its ancient church, associations with witchcraft folklore, and views over the River Crouch.
-
D.
Whittlesey
Whittlesey is a historic market town and civil parish in the Fenland area of Cambridgeshire, England, known for its traditional Straw Bear Festival and surrounding wetland landscapes.
-
E.
Twyford
Twyford is a village and civil parish in Berkshire, England, known as a commuter settlement between Reading and 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a755e88190a50126e2d1d6d4cb |
completed | March 27, 2026, 9:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ef11f76881909d802942c4013509 |
completed | March 28, 2026, 3:09 p.m. |
Created at: March 27, 2026, 3:03 p.m.