Triple
T9498538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet invasion and occupation |
E229074
|
entity |
| Predicate | targetGovernmentType |
P88957
|
FINISHED |
| Object | democratic republic |
—
|
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: democratic republic | Statement: [Soviet invasion and occupation, targetGovernmentType, democratic republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetGovernmentType Context triple: [Soviet invasion and occupation, targetGovernmentType, democratic republic]
-
A.
governmentalUnitType
Indicates the specific category or classification of a governmental unit (such as federal, state, municipal, or other administrative level) that an entity belongs to.
-
B.
typeOfGovernmentInstitution
Indicates that one entity is a government institution of the type or category specified by the other entity.
-
C.
governmentTypeServed
Indicates the type of government that an entity serves, is affiliated with, or operates under in its role or function.
-
D.
basedInGovernmentType
Indicates that an entity operates within or is associated with a government of a specified governmental system or type.
-
E.
governmentBodyType
Indicates the classification or category of a governmental organization based on its structural or functional 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ef06b88190b7a840caddea3e38 |
completed | April 1, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69cca5651a588190a3cfebe249a223e5 |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca8c6b0f081908334d6c7cf80e03c |
completed | April 1, 2026, 5:10 a.m. |
Created at: March 30, 2026, 7:56 p.m.