Triple
T2015156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regions of Belgium |
E43777
|
entity |
| Predicate | governanceScope |
P11585
|
FINISHED |
| Object | territorial matters |
—
|
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: territorial matters | Statement: [Regions of Belgium, governanceScope, territorial matters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governanceScope Context triple: [Regions of Belgium, governanceScope, territorial matters]
-
A.
organizationalScope
Indicates the range or extent of responsibility, authority, or applicability that an action, policy, or relationship has within an organization or its sub-units.
-
B.
governanceModel
Indicates the type or structure of authority, decision-making, and control that defines how an entity is directed and overseen.
-
C.
governanceArea
chosen
Indicates the geographic or jurisdictional area over which an entity has governing authority or responsibility.
-
D.
operationalScope
Indicates the range, extent, or boundaries within which an entity, process, or activity is authorized or designed to operate.
-
E.
organizationTypeGoverned
Indicates that one entity governs or has authoritative control over a specific type or category of organization.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8b610a88190bc10fd7dda19da08 |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.