Triple
T16545021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regulation (EU) 2021/819 |
E401918
|
entity |
| Predicate | hasDirectEffect |
P123985
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Regulation (EU) 2021/819, hasDirectEffect, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDirectEffect Context triple: [Regulation (EU) 2021/819, hasDirectEffect, yes]
-
A.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
B.
hasIntendedEffect
Indicates that one entity is expected or designed to produce a particular effect or outcome on another entity or context.
-
C.
hasCanonicalImpactOn
Indicates that one entity exerts a standard, authoritative, or officially recognized influence or effect on another entity.
-
D.
hasInteractionEffects
Indicates that one entity’s presence, action, or state alters, influences, or modifies the behavior, effect, or outcome associated with another entity.
-
E.
hasTypeOfEffect
Indicates that one entity produces, exhibits, or is associated with a particular kind or category of effect on another entity or context.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34560daf08190b353b415d8ab280d |
completed | April 18, 2026, 8:48 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:15 a.m.