Triple
T37321598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Revolutionary United Front |
E926493
|
entity |
| Predicate | committedWarCrimes |
P11256
|
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: [Revolutionary United Front, committedWarCrimes, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: committedWarCrimes Context triple: [Revolutionary United Front, committedWarCrimes, true]
-
A.
warCrimesContext
Indicates a context in which actions or events are associated with the commission, investigation, or adjudication of war crimes.
-
B.
associatedWithWarCrimePerpetrator
Indicates that an entity has a connection or involvement with an individual or group responsible for committing a war crime.
-
C.
associatedWithCrimesAgainstHumanity
Indicates a relationship in which an entity is linked or connected to the planning, commission, support, or responsibility for crimes against humanity.
-
D.
natureOfAtrocities
Indicates the specific type or character of atrocities associated with an event, action, or entity.
-
E.
committedCrime
chosen
Indicates that an entity has carried out or been responsible for a criminal act or offense.
- 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_69f76eb28af88190b093b32e3fd614ab |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.