Triple
T25666477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sint-Genesius-Rode |
E643532
|
entity |
| Predicate | isBilingualDeFacto |
P21622
|
FINISHED |
| Object | Dutch and French |
—
|
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 and French | Statement: [Sint-Genesius-Rode, isBilingualDeFacto, Dutch and French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBilingualDeFacto Context triple: [Sint-Genesius-Rode, isBilingualDeFacto, Dutch and French]
-
A.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
-
B.
isBilingualRegion
chosen
Indicates that a region officially uses two languages or has two predominant languages in regular use.
-
C.
isBinational
Indicates that an entity is associated with or recognized by two distinct nations, such as holding dual nationality or operating under the authority of two countries.
-
D.
isLinguaFrancaOf
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
-
E.
majorityBilingualWith
Indicates that the majority of individuals in a given group or population are bilingual in the two specified languages or language groups.
- 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_69e77e7e45648190a068ed3faa8016ea |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fb2e5e548190a0b3a84b02c07940 |
completed | May 2, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 7:05 p.m.