Triple
T26391802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet Guards units |
E663430
|
entity |
| Predicate | hadPriorityForEquipment |
P160493
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Soviet Guards units, hadPriorityForEquipment, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPriorityForEquipment Context triple: [Soviet Guards units, hadPriorityForEquipment, yes]
-
A.
hasEquipmentStatus
Indicates the current operational or condition state assigned to a piece of equipment.
-
B.
hasPriorityIssue
Indicates that an entity is associated with an issue that is marked as high or urgent priority.
-
C.
laterEquipment
Indicates that one piece of equipment occurs, is installed, or is used at a later time than another piece of equipment.
-
D.
intendedEquipmentType
Indicates that a particular piece of equipment is the planned or designated type to be used in a given context or activity.
-
E.
primaryEquipment
Indicates that one entity serves as the main or most important piece of equipment used by another entity.
- 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_69ee883823988190b418b111be28a44a |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f610c024f081908237794984538566 |
completed | May 2, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f5f800fa9c8190aab0962669fde8ac |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f6018ceb1c8190a6a5f84071659a96 |
completed | May 2, 2026, 1:52 p.m. |
Created at: April 26, 2026, 11:26 p.m.