Triple
T1713281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian party system |
E37232
|
entity |
| Predicate | mainLinguisticCleavage |
P32245
|
FINISHED |
| Object | Dutch‑speaking parties |
—
|
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 parties | Statement: [Belgian party system, mainLinguisticCleavage, Dutch‑speaking parties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainLinguisticCleavage Context triple: [Belgian party system, mainLinguisticCleavage, Dutch‑speaking parties]
-
A.
linguisticClassification
Indicates the relationship by which an entity is categorized according to its language or linguistic type.
-
B.
languageDiversity
Indicates the degree to which multiple distinct languages are present and used within a given context or population.
-
C.
linguisticIsolation
Indicates a condition where an entity is separated from others in terms of language, lacking shared or effective linguistic communication.
-
D.
macrolanguageGrouping
Indicates that one language is classified as part of a broader macrolanguage grouping that encompasses multiple closely related language varieties.
-
E.
macrolanguageOf
Indicates that one language functions as a macrolanguage encompassing or grouping together one or more related individual languages.
- F. None of above. chosen
Provenance (4 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab7521878c8190b9e7739b8c3fc705 |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61bd46d48190915500d75a9d8e94 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab752034348190a1cc20955ed24f6f |
completed | March 7, 2026, 12:45 a.m. |
Created at: March 4, 2026, 7:30 p.m.