Triple
T31794957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poor Law Union |
E811569
|
entity |
| Predicate | typicalUnitCount |
—
|
GENERATED |
| Object | several parishes |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUnitCount Context triple: [Poor Law Union, typicalUnitCount, several parishes]
-
A.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
B.
typicalUnitType
Indicates that one entity is the standard or commonly used unit type associated with measuring or expressing the other entity.
-
C.
typicalUnitConfiguration
Indicates the standard or commonly used arrangement, composition, or setup of a unit in a given context.
-
D.
typicalPackSize
Indicates the usual quantity of items contained together in a single package for that entity.
-
E.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
- F. None of above. chosen
Provenance (1 batch)
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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
Created at: April 30, 2026, 11:40 p.m.