Triple
T17561971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paraguayan Air Force |
E427712
|
entity |
| Predicate | hasSecondaryTask |
P78228
|
FINISHED |
| Object | support to ground forces |
—
|
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: support to ground forces | Statement: [Paraguayan Air Force, hasSecondaryTask, support to ground forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryTask Context triple: [Paraguayan Air Force, hasSecondaryTask, support to ground forces]
-
A.
hasSecondary
Indicates that an entity is associated with an additional or subordinate counterpart beyond its primary one.
-
B.
hasSecondaryCore
Indicates that an entity possesses an additional, subordinate core component alongside its primary core.
-
C.
hasSecond
Indicates that one entity is the second item, position, or element in an ordered sequence or pair relative to another entity.
-
D.
hasSecondarySubject
Indicates that an entity is associated with an additional, non-primary subject in a given context or relationship.
-
E.
hasSecondaryUsage
chosen
Indicates that an entity is associated with an additional, non-primary function or purpose beyond its main intended use.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e456274c888190ac80402e391674dd |
completed | April 19, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.