Triple
T5306552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNOSOM II |
E120115
|
entity |
| Predicate | includedCivilianComponent |
P63390
|
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: [UNOSOM II, includedCivilianComponent, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includedCivilianComponent Context triple: [UNOSOM II, includedCivilianComponent, true]
-
A.
isCivilian
Indicates that an entity is a non-military, non-combatant individual in the context of a given situation or system.
-
B.
civilianVariant
Indicates that one entity is a civilian version or non-military counterpart of another entity.
-
C.
hasCivilianClass
Indicates that an entity is associated with or belongs to a particular civilian classification or category.
-
D.
civilianTarget
Indicates that the action or operation is directed at, affects, or designates civilians or civilian objects as the target.
-
E.
civilianUse
Indicates that something is intended for, suitable for, or actually used by civilians rather than military or combat purposes.
- 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_69bd44704be88190acdb2ac481b0ff55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd86f20f008190be7b5848af05f2b8 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd84534f9c8190bc19d4812060768d |
completed | March 20, 2026, 5:30 p.m. |
| PDg | Predicate description generation | batch_69bd86f0cbfc8190b6665dd9b28d6345 |
completed | March 20, 2026, 5:42 p.m. |
Created at: March 20, 2026, 1:53 p.m.