Triple
T9557334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staffordshire–Shropshire border |
E230570
|
entity |
| Predicate | separatesType |
P1175
|
FINISHED |
| Object | non-metropolitan counties |
—
|
LITERAL 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: non-metropolitan counties | Statement: [Staffordshire–Shropshire border, separatesType, non-metropolitan counties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: separatesType Context triple: [Staffordshire–Shropshire border, separatesType, non-metropolitan counties]
-
A.
separates
chosen
Indicates that one entity divides, parts, or keeps other entities apart from each other.
-
B.
separatesBy
Indicates that one entity divides, partitions, or creates a boundary between two or more other entities.
-
C.
separationMethod
Indicates the technique or process used to separate one substance, component, or entity from another.
-
D.
separatedInto
Indicates that something has been divided or split into distinct parts, groups, or components.
-
E.
separatesAt
Indicates that one entity divides or splits another entity into distinct parts at a specific point, boundary, or location.
- F. None of above.
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_69ca847d3be8819099c9dad2a7e786f1 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9946c7b8819082f3a4ec4fc979e6 |
completed | April 1, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69ccd594d0ac8190a81bc11a3a538167 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:03 p.m.