Triple
T13240163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dockery Plantation |
E315258
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | cotton plantation |
C32698
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: cotton plantation Context triple: [Dockery Plantation, instanceOf, cotton plantation]
-
A.
former cotton plantation
A former cotton plantation is a historic agricultural estate where cotton was once cultivated, often using enslaved labor, now typically repurposed or preserved as a site of cultural, educational, or memorial significance.
-
B.
sugar plantation
A sugar plantation is a large agricultural estate dedicated to cultivating sugarcane (or sugar beets) and processing them into raw sugar, typically relying on intensive labor and monoculture practices.
-
C.
former rice plantation
A former rice plantation is a historic agricultural estate once dedicated to large-scale rice cultivation, often characterized by remnants of fields, irrigation systems, and associated buildings, now repurposed or abandoned.
-
D.
colonial-era plantation
A colonial-era plantation is a large agricultural estate established during the colonial period that relied on coerced or enslaved labor to produce cash crops for export, typically reinforcing systems of racial and economic exploitation.
-
E.
fictional plantation
A fictional plantation is an imagined large agricultural estate, often set in a specific historical or fantastical context, used in storytelling to explore themes of labor, power, culture, and social hierarchy.
- F. None of above. chosen
Provenance (1 batch)
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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
Created at: April 9, 2026, 9:23 p.m.