Triple
T334389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A44 road |
E6692
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Gloucestershire |
E11924
|
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: Gloucestershire | Statement: [A44 road, passesThrough, Gloucestershire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gloucestershire Context triple: [A44 road, passesThrough, Gloucestershire]
-
A.
Gloucestershire
chosen
Gloucestershire is a historic county in South West England known for its rural Cotswolds landscapes, cathedral city of Gloucester, and rich medieval heritage.
-
B.
Shropshire
Shropshire is a largely rural county in the West Midlands of England, known for its historic market towns, rolling countryside, and parts of the Shropshire Hills Area of Outstanding Natural Beauty.
-
C.
Dorset
Dorset is a rural county on England’s south coast, known for its Jurassic Coast World Heritage Site, rolling countryside, and historic market towns.
-
D.
Somerset
Somerset is a historic county in South West England known for its rural landscapes, coastal areas, and cities such as Bath and Wells.
-
E.
Hampshire
Hampshire is a county on England’s south coast known for its historic cities, naval and military heritage, and mix of rural countryside and coastal 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eac641708190b85fa21368e5de8e |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a52ea6ac6c8190820a6d88450909bd |
completed | March 2, 2026, 6:31 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.