Triple
T11130753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgium–Germany border |
E263271
|
entity |
| Predicate | languageZones |
P3950
|
FINISHED |
| Object | Dutch–German border area in the north |
—
|
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: Dutch–German border area in the north | Statement: [Belgium–Germany border, languageZones, Dutch–German border area in the north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageZones Context triple: [Belgium–Germany border, languageZones, Dutch–German border area in the north]
-
A.
languageZone
chosen
Indicates the linguistic region or area in which a language is predominantly used or officially recognized.
-
B.
languageArea
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
C.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
D.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
-
E.
languageFamilyRegion
Indicates the geographic region or area in which a language family is predominantly found or historically associated.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e831f4808190afabdaa0e97bbe32 |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.