Triple
T517430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laos |
E10737
|
entity |
| Predicate | mainEconomicSector |
P71
|
FINISHED |
| Object | agriculture |
—
|
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: agriculture | Statement: [Laos, mainEconomicSector, agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainEconomicSector Context triple: [Laos, mainEconomicSector, agriculture]
-
A.
economicClassification
Indicates how an entity is categorized based on its economic characteristics, status, or role within an economic system.
-
B.
economicSectorIssue
Indicates that there is a problem, challenge, or concern affecting a particular economic sector.
-
C.
isMajorIndustrialEconomy
Indicates that an entity is one of the world’s leading industrialized economies, characterized by large-scale industrial output and significant influence in global economic activity.
-
D.
sector
chosen
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
E.
economicFunction
Indicates the role or purpose an entity serves within an economic system, such as how it contributes to production, distribution, or consumption of goods and services.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f19d81d48190bd65a02059fc8473 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f0151e8c81909a82b58ac0515eba |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.