Triple
T17249103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Court of Appeal of Douai |
E418701
|
entity |
| Predicate | geographicalRegionServed |
P30177
|
FINISHED |
| Object | northern France |
—
|
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: northern France | Statement: [Court of Appeal of Douai, geographicalRegionServed, northern France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicalRegionServed Context triple: [Court of Appeal of Douai, geographicalRegionServed, northern France]
-
A.
issuerRegionServed
Indicates the geographic region or area that the issuer provides services to or operates within.
-
B.
serviceRegion
chosen
Indicates the geographic area or jurisdiction within which a service is provided or applicable.
-
C.
destinationCountryServed
Indicates that a given entity (such as a service, route, or provider) serves or operates to a specified destination country.
-
D.
geographicAreaOfSupport
Indicates the geographic region or area within which support, assistance, or services are provided or applicable.
-
E.
hasCountryServed
Indicates that a person or organization has provided service to, or performed duties on behalf of, a specified 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e2636f48190b29548ff80402bef |
completed | April 19, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_69e3832553ac819091aa917c84f755b6 |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.