Triple
T5571488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 本間雅晴 |
E146211
|
entity |
| Predicate | 有罪判決 |
P6201
|
FINISHED |
| Object | 戦争犯罪 |
—
|
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: 戦争犯罪 | Statement: [本間雅晴, 有罪判決, 戦争犯罪]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 有罪判決 Context triple: [本間雅晴, 有罪判決, 戦争犯罪]
-
A.
convictedOf
chosen
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
B.
sentencedTo
Indicates that an authority has officially assigned a specific punishment or penalty to an entity, typically as the outcome of a legal or disciplinary process.
-
C.
convictedBy
Indicates that an authority, typically a court or judge, has formally found an entity guilty of a crime or offense.
-
D.
convictedIndividual
Indicates that an individual has been found guilty of a crime or offense through a formal legal process and has received a conviction.
-
E.
reasonForConviction
Indicates the specific offense or legal basis for which an individual was found guilty or convicted.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020502a288190af37f9ebb88fccae |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b147cc081909237f3f2967d4cb8 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:37 p.m.