Triple
T8868686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Niger |
E211087
|
entity |
| Predicate | economySectorMajor |
P16022
|
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: [Republic of Niger, economySectorMajor, agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economySectorMajor Context triple: [Republic of Niger, economySectorMajor, agriculture]
-
A.
economicSectorSourceOfWealth
chosen
Indicates that a particular economic sector is the primary source from which an entity derives its wealth or income.
-
B.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
C.
economicSectorIssue
Indicates that there is a problem, challenge, or concern affecting a particular economic sector.
-
D.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
E.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial 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_69ca838d3c7c8190a849566d5afd2b11 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61241d048190aead14a8f5589856 |
completed | April 1, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2956788190a311c647b4da17a6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:51 p.m.