Triple
T19870965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eritrean economy |
E477514
|
entity |
| Predicate | mainExportSector |
P3026
|
FINISHED |
| Object | mining |
—
|
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: mining | Statement: [Eritrean economy, mainExportSector, mining]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainExportSector Context triple: [Eritrean economy, mainExportSector, mining]
-
A.
majorExport
chosen
Indicates that something is a primary or significant export product or resource of a given entity (such as a country or region).
-
B.
economicSectorDominant
Indicates that one economic sector holds a leading or controlling position relative to others in terms of influence, output, or importance.
-
C.
sectoralCoverage
Indicates the specific sectors, industries, or domains to which something (such as a policy, agreement, or dataset) applies or extends.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
targetsSector
Indicates that an entity is directed toward, focused on, or intended to affect a particular economic or industry sector.
- 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_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. |
Created at: April 10, 2026, 1:51 p.m.