Triple
T19870970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eritrean economy |
E477514
|
entity |
| Predicate | mainImportCategory |
P137652
|
FINISHED |
| Object | food |
—
|
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: food | Statement: [Eritrean economy, mainImportCategory, food]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainImportCategory Context triple: [Eritrean economy, mainImportCategory, food]
-
A.
coreCategory
Indicates that one entity is the primary or fundamental category to which another entity belongs or is classified under.
-
B.
primaryImports
Indicates that one entity is the main or predominant source from which another entity imports goods, services, or resources.
-
C.
canonicalCategory
Indicates that an entity is assigned to its primary or standard category within a classification system.
-
D.
majorImport
Indicates that one entity is a primary or significant source of imported goods or resources for another entity.
-
E.
mainExpenditureCategory
Indicates the primary type or classification of spending to which a particular expenditure mainly belongs.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658a3d2b08190ad81914d4860df0e |
completed | April 20, 2026, 4:47 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:51 p.m.