Triple
T10170607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prosecutor v. Théoneste Bagosora |
E235320
|
entity |
| Predicate | sentenceOnAppeal |
P20881
|
FINISHED |
| Object | 35 years imprisonment |
—
|
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: 35 years imprisonment | Statement: [Prosecutor v. Théoneste Bagosora, sentenceOnAppeal, 35 years imprisonment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentenceOnAppeal Context triple: [Prosecutor v. Théoneste Bagosora, sentenceOnAppeal, 35 years imprisonment]
-
A.
appeal
Indicates that one party formally requests a higher authority to review, reconsider, or overturn a prior decision, judgment, or outcome.
-
B.
sentencedOn
Indicates that a judicial authority has formally imposed a legal sentence or punishment on an entity on a specific date.
-
C.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
D.
sentence
Indicates that one entity is a sentence that expresses, contains, or encodes information about another entity.
-
E.
sentencedTo
chosen
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.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9d36608190be78665cc3410cf2 |
completed | April 2, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.