Triple
T290352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kent |
E5977
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | East Sussex |
E25825
|
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: East Sussex | Statement: [Kent, borders, East Sussex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: East Sussex Context triple: [Kent, borders, East Sussex]
-
A.
East Sussex
chosen
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.
-
B.
West Sussex
West Sussex is a county in South East England known for its mix of coastal towns, rural countryside, and historic market settlements.
-
C.
Essex
Essex is a county in the east of England, known for its mix of rural landscapes, historic towns, and proximity to London.
-
D.
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.
-
E.
Norfolk County
Norfolk County is a county in eastern Massachusetts that includes a mix of suburban communities and key urban institutions just outside Boston.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e4f78bc81909a64fd6aaec3b504 |
completed | Feb. 28, 2026, 3:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4777638a88190af189b8a3f972610 |
completed | March 1, 2026, 5:29 p.m. |
Created at: Feb. 28, 2026, 3:02 a.m.