Triple
T38314966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EFDD |
E1033798
|
entity |
| Predicate | mepCountAtPeak |
P4549
|
FINISHED |
| Object | over 40 Members of the European Parliament |
—
|
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: over 40 Members of the European Parliament | Statement: [EFDD, mepCountAtPeak, over 40 Members of the European Parliament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mepCountAtPeak Context triple: [EFDD, mepCountAtPeak, over 40 Members of the European Parliament]
-
A.
memberCountAtPeak
chosen
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
B.
numberOfEmployeesAtPeak
Indicates the highest recorded count of employees that an entity had at any point in time.
-
C.
hasNumberOfSeatsAtPeak
Indicates the maximum number of seats available or occupied at the peak usage or capacity of something.
-
D.
deploymentPeakNumber
Indicates the maximum number of deployments (or deployment instances) reached during a specified period or under given conditions.
-
E.
numberOfLocationsAtPeak
Indicates the total count of distinct locations associated with an entity at its highest or peak point in time or activity.
- 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_69f76e132c408190969b3d35c04b87ae |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.