Triple
T21799917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheriffdom of Grampian, Highland and Islands |
E538209
|
entity |
| Predicate | numberOfSheriffCourts |
P4502
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Sheriffdom of Grampian, Highland and Islands, numberOfSheriffCourts, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSheriffCourts Context triple: [Sheriffdom of Grampian, Highland and Islands, numberOfSheriffCourts, multiple]
-
A.
numberOfCourts
chosen
Indicates the quantity of courts associated with or present at a given entity or location.
-
B.
numberOfRegionalCourts
Indicates the total count of regional courts associated with a given entity.
-
C.
numberOfCourtrooms
Indicates the total count of courtrooms associated with a given legal facility, jurisdiction, or court entity.
-
D.
numberOfJurisdictions
Indicates the count of distinct legal or administrative jurisdictions associated with or applicable to an entity or situation.
-
E.
hasCourts
Indicates that an entity possesses, contains, or is equipped with one or more courts (e.g., legal, sports, or judicial facilities).
- 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f077fede848190b8fe07941d6573d9 |
completed | April 28, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:53 p.m.