Triple
T33330043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Kishida Cabinet |
E853376
|
entity |
| Predicate | hasNumberOfWomenMinisters |
P196711
|
FINISHED |
| Object | 3 |
—
|
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 | Statement: [First Kishida Cabinet, hasNumberOfWomenMinisters, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfWomenMinisters Context triple: [First Kishida Cabinet, hasNumberOfWomenMinisters, 3]
-
A.
hasNumberOfMinisters
Indicates the specific count of ministers associated with an entity, such as a government, cabinet, or organization.
-
B.
hasFemaleLeader
Indicates that the subject entity is led or governed by a woman in a primary leadership role.
-
C.
hasMinister
Indicates that one entity serves as the minister (political, religious, or administrative official) responsible for or associated with another entity.
-
D.
hasMinisterialMembers
Indicates that an entity includes or is associated with members who hold ministerial positions or roles.
-
E.
hasLayMinisters
Indicates that an entity includes or is served by lay ministers (non-ordained individuals performing ministerial roles).
- 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_69f34969614c81909cd99661b0902533 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe629b4fa481908467c7c41b77f0c6 |
completed | May 8, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69fe61bb260c819083f9378a3a06ca47 |
completed | May 8, 2026, 10:20 p.m. |
| PDg | Predicate description generation | batch_69fe629a8d4c8190b4aa4dee39efc0a6 |
completed | May 8, 2026, 10:24 p.m. |
Created at: May 1, 2026, 1:34 a.m.