Triple
T38276189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brussels–Namur |
E1021961
|
entity |
| Predicate | languageRegionCrossed |
P53840
|
FINISHED |
| Object | Dutch-speaking area |
—
|
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-speaking area | Statement: [Brussels–Namur, languageRegionCrossed, Dutch-speaking area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageRegionCrossed Context triple: [Brussels–Namur, languageRegionCrossed, Dutch-speaking area]
-
A.
crossBorderLanguage
Indicates a language that is used across national borders, linking communities in more than one country.
-
B.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
-
C.
languageBarrierWith
Indicates that communication between the two entities is hindered or obstructed due to differences in language.
-
D.
alsoInLanguageRegion
chosen
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
E.
languageRegionFocus
Indicates that something (such as a work, resource, or activity) is primarily concerned with or targeted toward a specific geographic region in terms of language use or linguistic focus.
- 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a0205c0bff481908238a382459b3a93 |
completed | May 11, 2026, 4:37 p.m. |
| PD | Predicate disambiguation | batch_6a0205143f20819087ee31576835be26 |
completed | May 11, 2026, 4:34 p.m. |
Created at: May 3, 2026, 4:30 p.m.