Triple
T10342375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EU economic governance framework |
E243155
|
entity |
| Predicate | setsReferenceValue |
P93790
|
FINISHED |
| Object | 3% of GDP general government deficit limit |
—
|
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: 3% of GDP general government deficit limit | Statement: [EU economic governance framework, setsReferenceValue, 3% of GDP general government deficit limit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setsReferenceValue Context triple: [EU economic governance framework, setsReferenceValue, 3% of GDP general government deficit limit]
-
A.
setWith
Indicates that one entity is grouped, combined, or associated together in a set or collection with another entity.
-
B.
settingRelation
Indicates a contextual relationship where one entity serves as the environment, backdrop, or situational context in which another entity exists or an event occurs.
-
C.
setsToOne
Indicates that an operation or condition forces a value, state, or variable to become exactly one.
-
D.
setsOut
Indicates that an entity begins a journey, course of action, or process, moving from an initial state or location toward a goal or destination.
-
E.
set
Indicates that an entity places, positions, or establishes another entity into a particular state, configuration, or location.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e91fdb2081909866c6ecf417d75a |
completed | April 7, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69d4df9dc3208190bf1bd106f44f6202 |
completed | April 7, 2026, 10:42 a.m. |
| PDg | Predicate description generation | batch_69d4e91ce2008190af252c140370b7f2 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 11:55 a.m.