Triple
T34952216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor of the Ostmark |
E1008029
|
entity |
| Predicate | linkedToCrimeType |
P7957
|
FINISHED |
| Object | war crimes |
—
|
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: war crimes | Statement: [Governor of the Ostmark, linkedToCrimeType, war crimes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToCrimeType Context triple: [Governor of the Ostmark, linkedToCrimeType, war crimes]
-
A.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
B.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
criminalAssociation
Indicates that one entity is involved with another in planning, facilitating, or participating in criminal activities or an organized crime group.
-
E.
isRelatedCriminalMatterOf
Indicates that one legal case or issue is connected to, arises from, or is otherwise associated with another in a criminal context.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
Created at: May 3, 2026, 4 p.m.