Triple
T18064584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | People's Army of Albania |
E432263
|
entity |
| Predicate | foreignModel |
P97305
|
FINISHED |
| Object | Soviet military model |
—
|
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: Soviet military model | Statement: [People's Army of Albania, foreignModel, Soviet military model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foreignModel Context triple: [People's Army of Albania, foreignModel, Soviet military model]
-
A.
foreignRelation
Indicates that there exists a diplomatic or international relationship between one entity and another entity from a different country or jurisdiction.
-
B.
linkedModel
Indicates that one model is associated or connected to another model, typically to reference or reuse its structure or behavior.
-
C.
associatedWithModel
chosen
Indicates that one entity has a defined connection, linkage, or relationship with a particular model.
-
D.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
E.
usedByModel
Indicates that something (such as a resource, method, or component) is utilized or consumed by a particular model.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4cce74a0c81908375e3100c7578b8 |
completed | April 19, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e3f90c652481908133a73106d78919 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:26 a.m.