Triple
T13066673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forces Patriotiques pour la Libération du Congo |
E329342
|
entity |
| Predicate | usedSexualViolence |
P14172
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Forces Patriotiques pour la Libération du Congo, usedSexualViolence, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedSexualViolence Context triple: [Forces Patriotiques pour la Libération du Congo, usedSexualViolence, true]
-
A.
usedViolenceAgainst
Indicates that one entity intentionally inflicted physical force or harm upon another entity.
-
B.
typeOfVictimization
Indicates the specific kind or category of harmful act, abuse, or exploitation experienced by a victim.
-
C.
hasTypeOfViolence
chosen
Indicates that an entity involves, exhibits, or is characterized by a specific kind or category of violent behavior or action.
-
D.
typeOfAbuse
Indicates the specific kind or category of abusive behavior that one entity inflicts on another.
-
E.
periodOfAbuse
Indicates the time span during which abusive behavior occurred or was experienced.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980eb81948190b27eb9ae19978079 |
completed | April 10, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 8:59 p.m.