Triple
T1036508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terrell County, Georgia |
E22374
|
entity |
| Predicate | hasEconomyType |
P1099
|
FINISHED |
| Object | agricultural |
—
|
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: agricultural | Statement: [Terrell County, Georgia, hasEconomyType, agricultural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEconomyType Context triple: [Terrell County, Georgia, hasEconomyType, agricultural]
-
A.
hasEconomyRankContext
Indicates the contextual basis or framework within which an entity’s economy rank is defined, interpreted, or compared.
-
B.
hasEconomicOrganization
Indicates that an entity possesses, is associated with, or participates in a specific economic organization or institutional economic structure.
-
C.
hasEconomicRole
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
-
D.
hasEconomicActivity
chosen
Indicates that an entity engages in, supports, or is associated with a specific type of economic activity or business operation.
-
E.
hasCapitalType
Indicates that a specified location’s capital is of a particular type (e.g., political, administrative, or economic capital).
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b729f8488190b2042bd9c625a833 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:41 p.m.