Triple
T10408721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Post-Soviet states |
E245331
|
entity |
| Predicate | hasCommonIssue |
P92967
|
FINISHED |
| Object | economic restructuring after 1991 |
—
|
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: economic restructuring after 1991 | Statement: [Post-Soviet states, hasCommonIssue, economic restructuring after 1991]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonIssue Context triple: [Post-Soviet states, hasCommonIssue, economic restructuring after 1991]
-
A.
hadIssue
Indicates that an entity experienced, encountered, or was affected by a particular problem, defect, or difficulty.
-
B.
hasSharedManagementIssue
chosen
Indicates that two or more entities are affected by the same management-related problem or concern.
-
C.
hasInternalIssue
Indicates that an entity is experiencing a problem, fault, or malfunction originating within itself or its internal components or processes.
-
D.
facingIssue
Indicates that an entity is currently experiencing, encountering, or dealing with a problem, difficulty, or obstacle.
-
E.
hasPracticeIssue
Indicates that an entity is associated with a specific problem, concern, or challenge arising in practical or real-world practice.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9faa97c819092cadedadabe26bf |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb6f160819090040644a12395ec |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:09 p.m.