Triple
T37536178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prosecutor v. Bosco Ntaganda |
E933202
|
entity |
| Predicate | armedGroupsInvolved |
P45966
|
FINISHED |
| Object | Union des Patriotes Congolais |
—
|
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: Union des Patriotes Congolais | Statement: [Prosecutor v. Bosco Ntaganda, armedGroupsInvolved, Union des Patriotes Congolais]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armedGroupsInvolved Context triple: [Prosecutor v. Bosco Ntaganda, armedGroupsInvolved, Union des Patriotes Congolais]
-
A.
armedGroupInvolved
chosen
Indicates that an armed group participated in, contributed to, or was otherwise involved in the referenced event or action.
-
B.
armedGroup
Indicates that an entity is an organized group equipped with weapons and capable of using armed force.
-
C.
factionInvolved
Indicates that a particular faction participates in, is associated with, or plays a role in the specified event, situation, or context.
-
D.
involvedForcesType
Indicates the type or category of forces that participate in or are associated with a given event, interaction, or situation.
-
E.
armedForcesInvolved
Indicates that the relationship or event involves the participation or presence of military or armed forces.
- 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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.