Triple
T37497521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prosecutor v. Germain Katanga |
E931868
|
entity |
| Predicate | crimeBase |
P7957
|
FINISHED |
| Object | murder |
—
|
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: murder | Statement: [Prosecutor v. Germain Katanga, crimeBase, murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crimeBase Context triple: [Prosecutor v. Germain Katanga, crimeBase, murder]
-
A.
crimeLocation
Indicates that a crime occurred at, or is associated with, a particular location.
-
B.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
C.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
D.
criminalFront
Indicates a relationship where one entity secretly operates as a cover or façade to conceal the illegal activities of another entity.
-
E.
crimeAgainst
Indicates that one entity commits or is responsible for a criminal act directed toward another entity.
- 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.