Triple
T709764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cumbria |
E14179
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Cumberland |
E53833
|
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: Cumberland | Statement: [Cumbria, contains, Cumberland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cumberland Context triple: [Cumbria, contains, Cumberland]
-
A.
Cumberland
chosen
Cumberland is a historic county in northwestern England, bordering Scotland and encompassing part of the Lake District.
-
B.
Calvert
Calvert is a given name most notably borne by Calvert Vaux, the 19th-century British-American architect and landscape designer who co-designed New York City's Central Park.
-
C.
Galloway
Galloway is a historic region in southwestern Scotland known for its rugged coastline, rural landscapes, and medieval ties to powerful Scottish clans.
-
D.
Brunswick
Brunswick is a historic city in northern Germany known for its medieval heritage and as the birthplace of mathematician Carl Friedrich Gauss.
-
E.
Rutland
Rutland is a small historic county in the East Midlands of England, known for its rural character and Rutland Water reservoir.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a55b63988190837e71fcdf3e39a6 |
completed | March 1, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a64a5851548190adeacb2feb35a1cb |
completed | March 3, 2026, 2:41 a.m. |
Created at: March 1, 2026, 7:36 p.m.