Triple
T3746343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ottoman air units |
E81219
|
entity |
| Predicate | receivedTrainingFrom |
P36609
|
FINISHED |
| Object | German military advisors |
—
|
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: German military advisors | Statement: [Ottoman air units, receivedTrainingFrom, German military advisors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivedTrainingFrom Context triple: [Ottoman air units, receivedTrainingFrom, German military advisors]
-
A.
hasTrained
chosen
Indicates that one entity has provided training or instruction to another entity.
-
B.
receivedSupportFrom
Indicates that one entity obtained help, resources, or backing from another entity.
-
C.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
-
D.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
E.
receivedFor
Indicates that something was obtained, accepted, or taken into possession on behalf of or for the benefit of a specified 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb69887c8190a3f1188ec85727b0 |
completed | March 8, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69adc04adebc819088d7f36d0ac343a6 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.