Triple
T4253837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riverside College |
E95922
|
entity |
| Predicate | regionServed |
P82
|
FINISHED |
| Object | Cheshire |
E17454
|
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: Cheshire | Statement: [Riverside College, regionServed, Cheshire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheshire Context triple: [Riverside College, regionServed, Cheshire]
-
A.
Cheshire
chosen
Cheshire is a ceremonial and historic county in North West England known for its rural landscapes, affluent towns, and production of Cheshire cheese.
-
B.
Cheshire
Cheshire is a small rural town in Berkshire County, Massachusetts, known for its scenic setting in the Berkshire Hills and its historic New England character.
-
C.
Cheshire East
Cheshire East is a unitary authority area in North West England, encompassing a mix of towns and rural communities and forming part of the wider Cheshire county.
-
D.
Staffordshire
Staffordshire is a landlocked county in the West Midlands of England known for its industrial heritage, particularly in pottery and brewing, and its mix of rural landscapes and historic towns.
-
E.
Somerset
Somerset is a historic county in South West England known for its rural landscapes, coastal areas, and cities such as Bath and Wells.
- 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ebe6fbc8190a89269b478b3f435 |
completed | March 12, 2026, 11:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a8845e6081908bbf1aef2a2da754 |
completed | March 14, 2026, 6:27 p.m. |
Created at: March 12, 2026, 11:06 p.m.