Triple
T18791039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army Reserve Technicians |
E459513
|
entity |
| Predicate | rankRelationship |
P59486
|
FINISHED |
| Object | military grade is tied to technician position |
—
|
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: military grade is tied to technician position | Statement: [Army Reserve Technicians, rankRelationship, military grade is tied to technician position]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankRelationship Context triple: [Army Reserve Technicians, rankRelationship, military grade is tied to technician position]
-
A.
rankEquivalent
Indicates that two entities hold the same rank or hierarchical level within a given ordering or classification system.
-
B.
rankingScope
chosen
Indicates the context or domain within which a ranking is defined, interpreted, or applied.
-
C.
rankingRole
Indicates that one entity holds a specific position or level in an ordered hierarchy or ranking relative to others.
-
D.
rankType
Indicates the specific category or classification of a rank within a ranking or hierarchy system.
-
E.
rankComparedTo
Indicates the relative ordering or position of one entity in comparison to another based on a specified ranking criterion.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5978599008190aaceaff1b1e0a2c7 |
completed | April 20, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.