Triple
T27533060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernissart |
E695022
|
entity |
| Predicate | municipalGovernmentLevel |
P1085
|
FINISHED |
| Object | local |
—
|
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: local | Statement: [Bernissart, municipalGovernmentLevel, local]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: municipalGovernmentLevel Context triple: [Bernissart, municipalGovernmentLevel, local]
-
A.
hasMunicipalLevel
Indicates that an entity is associated with a specific level or tier within a municipal (local government) hierarchy.
-
B.
levelOfGovernment
chosen
Indicates the specific tier or layer within a governmental hierarchy (e.g., local, regional, national) at which an entity operates or an action is taken.
-
C.
municipalScope
Indicates that something falls within the authority, jurisdiction, or functional domain of a municipality or local city government.
-
D.
municipality
Indicates that one entity is a municipality (a local administrative unit) in which the other entity is located or which it governs.
-
E.
cityGovernment
Indicates that a city’s governing authority has jurisdiction, control, or administrative responsibility over the referenced entity.
- 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_69ef538608b081908b9f659bb09d5e0f |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 27, 2026, 1:27 p.m.