Triple
T7356652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erewash |
E169642
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Borrowash |
E117168
|
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: Borrowash | Statement: [Erewash, contains, Borrowash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borrowash Context triple: [Erewash, contains, Borrowash]
-
A.
Borrowash
chosen
Borrowash is a large village in the county of Derbyshire, England, situated just east of the city of Derby.
-
B.
Borenore
Borenore is a small rural locality in the Central West region of New South Wales, Australia, known for its agricultural surroundings and nearby limestone caves.
-
C.
Banwen
Banwen is a small village in South Wales, known historically for its coal mining heritage and location near the upper Dulais Valley.
-
D.
Bisham
Bisham is a village in Berkshire, England, known for its historic riverside setting on the River Thames and proximity to the town of Marlow.
-
E.
Borrisokane
Borrisokane is a small rural town in northern County Tipperary, Ireland, known for its agricultural surroundings and traditional Irish community character.
- 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f13a62e48190a2d1781a630aa9f0 |
completed | March 27, 2026, 9:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7faa6a5d88190b969b7783edc67b7 |
completed | March 28, 2026, 3:58 p.m. |
Created at: March 27, 2026, 3:06 p.m.