Triple
T733988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auschwitz III-Monowitz |
E14890
|
entity |
| Predicate | victimOfCrimeType |
P7957
|
FINISHED |
| Object | crimes against humanity |
—
|
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 humanity | Statement: [Auschwitz III-Monowitz, victimOfCrimeType, crimes against humanity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimOfCrimeType Context triple: [Auschwitz III-Monowitz, victimOfCrimeType, crimes against humanity]
-
A.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
B.
victimGroup
Indicates that one group or entity is the target or recipient of harm, abuse, or wrongdoing caused by another.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
victimOccupation
Indicates the profession or job role held by the person who is the victim in an event or incident.
-
E.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fafee081909bf356854c09aaff |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.