Triple
T24429879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anton Tobias |
E615966
|
entity |
| Predicate | causeOfViolence |
P155891
|
FINISHED |
| Object | demonic possession of his hand |
—
|
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: demonic possession of his hand | Statement: [Anton Tobias, causeOfViolence, demonic possession of his hand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfViolence Context triple: [Anton Tobias, causeOfViolence, demonic possession of his hand]
-
A.
typeOfViolenceAddressed
Indicates the specific form or category of violence that is being targeted, dealt with, or addressed in a given context.
-
B.
hasTypeOfViolence
Indicates that an entity involves, exhibits, or is characterized by a specific kind or category of violent behavior or action.
-
C.
violenceLedTo
Indicates that an act or state of violence caused or directly resulted in a subsequent event, condition, or outcome.
-
D.
usedViolenceAgainst
Indicates that one entity intentionally inflicted physical force or harm upon another entity.
-
E.
viewOnViolence
Indicates an entity’s stance, opinion, or attitude toward the use of violence.
- F. None of above. chosen
Provenance (4 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_69e2d7eadb248190a867130fe45f0388 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296aab8948190b9cb869bab71fb4c |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287cc4fd4819081e93cc638d9512d |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f2915233c48190a181c8c1924e892c |
completed | April 29, 2026, 11:16 p.m. |
Created at: April 18, 2026, 2:15 a.m.