Triple
T30542099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | labour courts of Belgium |
E777305
|
entity |
| Predicate | hasLayJudgesRepresenting |
P73792
|
FINISHED |
| Object | employers |
—
|
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: employers | Statement: [labour courts of Belgium, hasLayJudgesRepresenting, employers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayJudgesRepresenting Context triple: [labour courts of Belgium, hasLayJudgesRepresenting, employers]
-
A.
usesLayJudges
chosen
Indicates that a legal system, court, or trial incorporates lay judges—non-professional, typically citizen adjudicators—into its decision-making process.
-
B.
hasJudges
Indicates that one entity serves as a judge or panel of judges for another entity, such as an event, competition, or legal case.
-
C.
hasJudge
Indicates that a legal case, proceeding, or decision is presided over or decided by a particular judge.
-
D.
hasJudgeFrom
Indicates that an entity has a judge whose origin, affiliation, or source is from a specified place or organization.
-
E.
hasPrincipalJudge
Indicates that one entity serves as the main or presiding judge for another entity, such as a court or judicial body.
- 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_69f2249d183c8190b79937c1768d2163 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdb45537288190b6791078d4a6899f |
completed | May 8, 2026, 10 a.m. |
| PD | Predicate disambiguation | batch_69fdb39ad96481908376d7def9fafc13 |
completed | May 8, 2026, 9:57 a.m. |
Created at: April 29, 2026, 8:19 p.m.