Triple
T1654148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navy Ministry of Japan |
E35758
|
entity |
| Predicate | hadCabinetRank |
P1269
|
FINISHED |
| Object | cabinet-level ministry |
—
|
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: cabinet-level ministry | Statement: [Navy Ministry of Japan, hadCabinetRank, cabinet-level ministry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadCabinetRank Context triple: [Navy Ministry of Japan, hadCabinetRank, cabinet-level ministry]
-
A.
hasCabinet
Indicates that one entity possesses, includes, or is equipped with a cabinet associated with it.
-
B.
cabinetLevel
chosen
Indicates that an official, position, or body holds a status equivalent to or recognized as part of a national cabinet-level rank or authority.
-
C.
servedInCabinetOf
Indicates that one person held a position as a member of the governmental cabinet led by another person.
-
D.
cabinetNumberInHistory
Indicates the specific cabinet number assigned to an entity within a historical record or context.
-
E.
hasRankCategory
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
- 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_69a8860568888190a32cd9f70acbba42 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf3359ce48190803b322db8ad6027 |
completed | March 6, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69a907cff53c8190b424f088478d3e2c |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:29 p.m.