Triple
T31546030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taba commune |
E804874
|
entity |
| Predicate | perpetratorInCase |
P172577
|
FINISHED |
| Object | Jean-Paul Akayesu |
—
|
NE NERFINISHED |
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: Jean-Paul Akayesu | Statement: [Taba commune, perpetratorInCase, Jean-Paul Akayesu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perpetratorInCase Context triple: [Taba commune, perpetratorInCase, Jean-Paul Akayesu]
-
A.
perpetratorType
Indicates the classification or category of the entity that carried out or is responsible for a harmful, illegal, or otherwise wrongful act.
-
B.
perpetratorStatus
Indicates the role or condition of an individual in relation to committing or being responsible for a specific harmful or criminal act.
-
C.
perpetratedBy
Indicates that an action, event, or wrongdoing was carried out or caused by a particular agent or entity.
-
D.
perpetratorTrial
Indicates that a legal trial is conducted to judge the actions or guilt of the identified perpetrator.
-
E.
perpetratorDescription
Indicates that the subject provides a textual description or characterization of the perpetrator involved in an act or incident.
- 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_69f348d11a048190a65eb8384a3754ac |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ac1ed23c8190ace57ffc9d8a3dc6 |
completed | May 3, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69f6aba8fba48190bc1a17117244cae1 |
completed | May 3, 2026, 1:58 a.m. |
Created at: April 30, 2026, 10:08 p.m.