Triple
T4082095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Title V – The Federal Government |
E87498
|
entity |
| Predicate | hasHigherNorm |
P52900
|
FINISHED |
| Object | no norm higher within Belgian domestic law |
—
|
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: no norm higher within Belgian domestic law | Statement: [Title V – The Federal Government, hasHigherNorm, no norm higher within Belgian domestic law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHigherNorm Context triple: [Title V – The Federal Government, hasHigherNorm, no norm higher within Belgian domestic law]
-
A.
hasNorm
Indicates that an entity is associated with, governed by, or characterized through a particular norm, rule, or standard.
-
B.
isHigherThan
Indicates that one entity has a greater value, level, or position than another entity.
-
C.
hasHigherClass
Indicates that one entity belongs to a higher rank, level, or category in a hierarchy than another entity.
-
D.
hasHigherStyleThan
Indicates that one entity’s style is considered superior or more fashionable than another’s.
-
E.
hasHigherDegree
Indicates that one entity possesses an academic degree that is of a higher level than the academic degree held by another entity.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc77dab481909bcf197daf2def59 |
completed | March 9, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9b34dec81909bbc3def9decc71a |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 9, 2026, 3:39 p.m.