Triple
T24191704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italian Army in World War II |
E599715
|
entity |
| Predicate | equipmentIssue |
P155623
|
FINISHED |
| Object | shortage of modern tanks |
—
|
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: shortage of modern tanks | Statement: [Italian Army in World War II, equipmentIssue, shortage of modern tanks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equipmentIssue Context triple: [Italian Army in World War II, equipmentIssue, shortage of modern tanks]
-
A.
equipmentLosses
Indicates the extent or instances of equipment that have been damaged, destroyed, or otherwise rendered unusable.
-
B.
platformIssue
Indicates that there is a problem, malfunction, or limitation affecting the operation or availability of a platform.
-
C.
equipmentProvider
Indicates that one entity supplies or makes available equipment for use by another entity.
-
D.
maintenanceFeature
Indicates that one entity serves as a maintenance-related feature, capability, or component associated with another entity.
-
E.
operatorTrainingIssue
Indicates that there is a problem, deficiency, or concern related to the training of an operator in performing a specific task or role.
- 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_69e288cdc8b88190bf2f835d3cb4ca28 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 17, 2026, 11:35 p.m.