Triple
T31794957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poor Law Union |
E811569
|
entity |
| Predicate | typicalUnitCount |
P207522
|
FINISHED |
| Object | several parishes |
—
|
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: several parishes | Statement: [Poor Law Union, typicalUnitCount, several parishes]
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 (4 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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 30, 2026, 11:40 p.m.