Triple
T33062436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prosecutor v. Théoneste Bagosora |
E846006
|
entity |
| Predicate | roleOfAccused |
P180567
|
FINISHED |
| Object | senior Rwandan military officer |
—
|
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: senior Rwandan military officer | Statement: [Prosecutor v. Théoneste Bagosora, roleOfAccused, senior Rwandan military officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfAccused Context triple: [Prosecutor v. Théoneste Bagosora, roleOfAccused, senior Rwandan military officer]
-
A.
coAccusedRole
Indicates that two or more entities share the status of being accused together in the same legal case or proceeding.
-
B.
accusedIn
Indicates that a person or entity is formally charged with wrongdoing in a particular case, proceeding, or context.
-
C.
accusedOf
Indicates that one entity has formally alleged or claimed that another entity committed a specific wrongdoing or offense.
-
D.
victimOfAccusation
Indicates that an entity is the target or subject of an accusation made by another party.
-
E.
hasAccusedRole
Indicates that one entity has the role or capacity of making an accusation against another entity.
- 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_69f3495333b8819095e9af56855b9061 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: May 1, 2026, 1:25 a.m.