Triple
T6280905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kidnapping and assault case involving Stompie Seipei |
E140777
|
entity |
| Predicate | victimEthnicity |
P10927
|
FINISHED |
| Object | Black South African |
—
|
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: Black South African | Statement: [kidnapping and assault case involving Stompie Seipei, victimEthnicity, Black South African]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimEthnicity Context triple: [kidnapping and assault case involving Stompie Seipei, victimEthnicity, Black South African]
-
A.
victimGroup
Indicates that one group or entity is the target or recipient of harm, abuse, or wrongdoing caused by another.
-
B.
victimRole
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
C.
coVictim
Indicates that two or more entities are victims in the same harmful event or incident.
-
D.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
E.
affectedEthnicGroup
chosen
Indicates that a particular ethnic group is impacted or influenced by an event, condition, policy, or action.
- 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063ddb3a4819083455f6da854f8a9 |
completed | March 22, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69c05608a5608190b22a1fdc4060470d |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:26 p.m.