Triple
T15764415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemish people |
E382180
|
entity |
| Predicate | demographicStatusInBelgium |
P120236
|
FINISHED |
| Object | largest linguistic group |
—
|
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: largest linguistic group | Statement: [Flemish people, demographicStatusInBelgium, largest linguistic group]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographicStatusInBelgium Context triple: [Flemish people, demographicStatusInBelgium, largest linguistic group]
-
A.
positionInBelgium
Indicates that one entity occupies a specific geographic location within the territory of Belgium.
-
B.
demographicStatusInRomania
Indicates the demographic status or classification of an entity within the population context of Romania.
-
C.
includesBelgianRegion
Indicates that one entity geographically or administratively contains or encompasses a region located in Belgium.
-
D.
passengerTrafficRankInBelgium
Indicates the relative position of an entity in terms of passenger traffic volume compared to other entities within Belgium.
-
E.
chartPositionBelgiumWallonia
Indicates the position or ranking of something on the music charts specifically in the Wallonia region of Belgium.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b6c9fc8190a1bcf763c4b04b12 |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e03cc871d0819085c0fc54de7984ff |
completed | April 16, 2026, 1:35 a.m. |
Created at: April 10, 2026, 4:47 a.m.