Triple
T37447213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Years of Lead |
E930580
|
entity |
| Predicate | mainTypeOfViolence |
P14172
|
FINISHED |
| Object | terrorism |
—
|
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: terrorism | Statement: [Years of Lead, mainTypeOfViolence, terrorism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainTypeOfViolence Context triple: [Years of Lead, mainTypeOfViolence, terrorism]
-
A.
typeOfViolenceAddressed
Indicates the specific form or category of violence that is being targeted, dealt with, or addressed in a given context.
-
B.
hasTypeOfViolence
chosen
Indicates that an entity involves, exhibits, or is characterized by a specific kind or category of violent behavior or action.
-
C.
violenceLevel
Indicates the degree or intensity of violent behavior, actions, or content present in or associated with an entity.
-
D.
typeOfVictimization
Indicates the specific kind or category of harmful act, abuse, or exploitation experienced by a victim.
-
E.
causeOfViolence
Indicates that one entity is the reason, trigger, or source leading to the occurrence of violence involving another 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_69f76ec0b9488190b7a4fae632bd1d2f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: May 3, 2026, 4:17 p.m.