Triple
T5265221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carsington Water |
E118921
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Ashbourne |
E141493
|
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: Ashbourne | Statement: [Carsington Water, near, Ashbourne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashbourne Context triple: [Carsington Water, near, Ashbourne]
-
A.
Ashbourne
chosen
Ashbourne is a historic market town in Derbyshire, England, known for its traditional architecture and annual Royal Shrovetide Football match.
-
B.
Ashby
Ashby is a small town in north-central Massachusetts, United States, known for its rural character and proximity to the city of Fitchburg.
-
C.
Ashby
Ashby is a surname most notably associated with Hal Ashby, the influential American film director known for 1970s classics such as "Harold and Maude" and "Being There."
-
D.
Ashover
Ashover is a rural village and civil parish in Derbyshire, England, known for its scenic countryside and historic stone buildings.
-
E.
Biddulph
Biddulph is a small town in Staffordshire, England, known historically for its coal mining and rural surroundings.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bf89ae481908835b711fb2696fd |
completed | March 20, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe8b787881909be9c01d1ba52561 |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:51 p.m.