Triple
T7452504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Public Prosecutor’s Office |
E172039
|
entity |
| Predicate | participatingMemberStatesCount |
P1590
|
FINISHED |
| Object | 22 |
—
|
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: 22 | Statement: [European Public Prosecutor’s Office, participatingMemberStatesCount, 22]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: participatingMemberStatesCount Context triple: [European Public Prosecutor’s Office, participatingMemberStatesCount, 22]
-
A.
numberOfMemberStates
chosen
Indicates the total count of member states associated with a given entity or organization.
-
B.
EUMemberState
Indicates that an entity is a country that is a member state of the European Union.
-
C.
subregionOfMemberStates
Indicates that one region is a subregion contained within, and belonging to, the member states of a larger political or organizational entity.
-
D.
numberOfRegionalMembers
Indicates the quantity of members associated with or belonging to a specific region within a given context.
-
E.
nonEuroMembersMayParticipateIn
Indicates that entities which are not members of the Euro area are allowed to take part in a specified activity, process, or arrangement.
- 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_69c68a66554c8190add75c65942c0317 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f38d6a8c8190af2e73c719da87a6 |
completed | March 27, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c6f039f7248190bb4183f97b605763 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:14 p.m.