Triple
T13002975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Local Government (Scotland) Act 1973 |
E322214
|
entity |
| Predicate | numberOfRegionsCreated |
P96073
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Local Government (Scotland) Act 1973, numberOfRegionsCreated, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRegionsCreated Context triple: [Local Government (Scotland) Act 1973, numberOfRegionsCreated, 9]
-
A.
numberOfNewRegions
chosen
Indicates the count of regions that have been newly created or added within a specified context or time frame.
-
B.
numberOfRegions
Indicates the total count of distinct regions associated with or contained within a given entity.
-
C.
regionNumberCreated
Indicates that a specific numbered region was created or established as a distinct area.
-
D.
regionNameCreated
Indicates that a specific region was created with the given name.
-
E.
numberOfProvinces
Indicates the total count of provinces associated with a given entity or within a specified region or country.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9a2a448190968833354280e474 |
completed | April 10, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69d97dc153a081909d13a694993f074a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:47 p.m.