Triple
T583692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rutte II cabinet |
E15110
|
entity |
| Predicate | numberOfCabinetMembers |
P15819
|
FINISHED |
| Object | 13 ministers |
—
|
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: 13 ministers | Statement: [Rutte II cabinet, numberOfCabinetMembers, 13 ministers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCabinetMembers Context triple: [Rutte II cabinet, numberOfCabinetMembers, 13 ministers]
-
A.
numberOfCommitteeMembers
Indicates the total count of individuals who are members of a given committee.
-
B.
numberOfSenators
Indicates the total count of senators associated with a given political body, region, or entity.
-
C.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
D.
totalNumberOfLegislators
Indicates the total count of legislators associated with a given political body, jurisdiction, or legislative session.
-
E.
officeHoldersNumber
Indicates the number of individuals who hold a particular office or position.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b8745c88190af9672e5fe8396c3 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494c9315c8190a773e8e00737d8a0 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985a2d08819090947895d9439e06 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.