Triple
T16016689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 山口那津男 |
E388484
|
entity |
| Predicate | 法曹資格 |
P5610
|
FINISHED |
| Object | 日本の弁護士資格 |
—
|
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: 日本の弁護士資格 | Statement: [山口那津男, 法曹資格, 日本の弁護士資格]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 法曹資格 Context triple: [山口那津男, 法曹資格, 日本の弁護士資格]
-
A.
legalEducationRequiredForPractice
Indicates that a specific type or level of legal education is required as a prerequisite for engaging in legal practice.
-
B.
studiedLawBy
Indicates that one entity pursued or received legal education under the instruction, supervision, or at the institution represented by the other entity.
-
C.
legalProfessionRole
chosen
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
D.
studiedLawIn
Indicates that a person received legal education or training at a particular institution or location.
-
E.
haveLaw
Indicates that a governing body or jurisdiction possesses, enforces, or is characterized by a particular law or set of laws.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:55 a.m.