Triple
T10657840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minnesota and Wisconsin |
E251140
|
entity |
| Predicate | shareEconomicSector |
P47145
|
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: [Minnesota and Wisconsin, shareEconomicSector, agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareEconomicSector Context triple: [Minnesota and Wisconsin, shareEconomicSector, agriculture]
-
A.
economicSectorDominant
Indicates that one economic sector holds a leading or controlling position relative to others in terms of influence, output, or importance.
-
B.
economicSectorSourceOfWealth
Indicates that a particular economic sector is the primary source from which an entity derives its wealth or income.
-
C.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
D.
associatedWithEconomicSector
chosen
Indicates that an entity has a connection or involvement with a particular economic sector, such as operating, participating, or being relevant within that sector.
-
E.
sectorInfluence
Indicates the degree to which one sector affects, shapes, or exerts control over another sector or over outcomes within that 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6e01643a88190abc7c16fd0f85e53 |
completed | April 8, 2026, 11:09 p.m. |
| PD | Predicate disambiguation | batch_69d6dd8753108190b799ffa0c760526e |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:07 p.m.