Triple
T13268092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuremberg Trials through Robert H. Jackson |
E315976
|
entity |
| Predicate | concernsCrimeType |
P7957
|
FINISHED |
| Object | crimes against peace |
—
|
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: crimes against peace | Statement: [Nuremberg Trials through Robert H. Jackson, concernsCrimeType, crimes against peace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concernsCrimeType Context triple: [Nuremberg Trials through Robert H. Jackson, concernsCrimeType, crimes against peace]
-
A.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
crimeRate
Indicates the frequency or level of criminal activity occurring within a given area or population.
-
C.
coversUpCrimeOf
Indicates that one entity conceals, protects, or hides the criminal actions or offenses committed by another entity.
-
D.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
E.
pursuesCrimeType
Indicates that an entity (such as a law enforcement body or individual) actively investigates, targets, or prosecutes a specified type of crime.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f60911081909fa346a054f76c9f |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:25 p.m.