Triple
T170353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Cam |
E3107
|
entity |
| Predicate | sourceRegion |
P410
|
FINISHED |
| Object |
Essex
Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
|
E30848
|
NE FINISHED |
How this triple was built (4 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: Essex | Statement: [River Cam, sourceRegion, Essex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Essex Context triple: [River Cam, sourceRegion, Essex]
-
A.
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.
-
B.
Essex County
Essex County is a historic coastal county in northeastern Massachusetts that includes cities such as Lynn, Salem, and Lawrence.
-
C.
Buckinghamshire
Buckinghamshire is a ceremonial and non-metropolitan county in South East England, known for its historic towns, Chiltern Hills countryside, and proximity to London.
-
D.
Cheshire
Cheshire is a ceremonial and historic county in North West England known for its rural landscapes, affluent towns, and production of Cheshire cheese.
-
E.
East Sussex
East Sussex is a county in South East England known for its English Channel coastline, the South Downs, and historic towns such as Hastings and Lewes.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Essex Triple: [River Cam, sourceRegion, Essex]
Generated description
Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Essex Target entity description: Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
-
A.
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.
-
B.
Essex County
Essex County is a historic coastal county in northeastern Massachusetts that includes cities such as Lynn, Salem, and Lawrence.
-
C.
Buckinghamshire
Buckinghamshire is a ceremonial and non-metropolitan county in South East England, known for its historic towns, Chiltern Hills countryside, and proximity to London.
-
D.
Cheshire
Cheshire is a ceremonial and historic county in North West England known for its rural landscapes, affluent towns, and production of Cheshire cheese.
-
E.
East Sussex
East Sussex is a county in South East England known for its English Channel coastline, the South Downs, and historic towns such as Hastings and Lewes.
- F. None of above. chosen
Provenance (5 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258b82bdc81908ebd50fb05d511df |
completed | Feb. 28, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3672cae0c819086233f16cc2003de |
completed | Feb. 28, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69a367aa62f481908414358a21667187 |
completed | Feb. 28, 2026, 10:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3686970ac81908ba7efe90feb26fd |
completed | Feb. 28, 2026, 10:12 p.m. |
Created at: Feb. 28, 2026, 2:34 a.m.