Triple
T23539951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rotherham Metropolitan Borough Council |
E577713
|
entity |
| Predicate | dividesAreaInto |
P99142
|
FINISHED |
| Object | electoral wards |
—
|
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: electoral wards | Statement: [Rotherham Metropolitan Borough Council, dividesAreaInto, electoral wards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dividesAreaInto Context triple: [Rotherham Metropolitan Borough Council, dividesAreaInto, electoral wards]
-
A.
dividesAreaApproximatelyEquallyBetween
Indicates that one entity partitions another entity’s area into parts that are roughly equal in size, though not necessarily exactly equal.
-
B.
dividesUrbanAreaInto
Indicates that one entity partitions or segments an urban area into distinct parts or zones.
-
C.
dividedBetween
Indicates that something is partitioned or shared among two or more distinct entities or groups.
-
D.
fieldDivision
Indicates a relationship where a larger field or area is partitioned into smaller sections or subdivisions.
-
E.
dividedIn
chosen
Indicates that one entity is partitioned or separated into multiple distinct parts, sections, or groups represented by another entity.
- 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae1a66b88190811b38523ea606fe |
completed | April 29, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69f118afabd88190bd88f49597d120e8 |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:10 p.m.