Triple
T18675034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel Sadashichi Doi |
E456578
|
entity |
| Predicate | languageOfMilitaryService |
P132251
|
FINISHED |
| Object | Japanese |
—
|
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: Japanese | Statement: [Colonel Sadashichi Doi, languageOfMilitaryService, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfMilitaryService Context triple: [Colonel Sadashichi Doi, languageOfMilitaryService, Japanese]
-
A.
militaryBranchLanguage
Indicates the language or languages officially used or primarily associated with a particular military branch.
-
B.
countryOfMilitaryService
Indicates that an entity served or is serving in the armed forces of a specified country.
-
C.
placeOfMilitaryService
Indicates the location or institution where a person performed their military service.
-
D.
hasMilitaryBranch
Indicates that an entity is associated with, served in, or is part of a specific branch of a military organization.
-
E.
militaryUnitTypeServed
Indicates that an entity served in, or was a member of, a specific type of military unit.
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556b4e390819091ad9dd118ca1f4f |
completed | April 19, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69e478db7a248190a8c6584673773923 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484133ee48190a80f1889d79f34c9 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:48 a.m.