Triple
T37066852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goochland County, Colony of Virginia |
E917468
|
entity |
| Predicate | hadPlantations |
P94035
|
FINISHED |
| Object | tobacco plantations |
—
|
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: tobacco plantations | Statement: [Goochland County, Colony of Virginia, hadPlantations, tobacco plantations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPlantations Context triple: [Goochland County, Colony of Virginia, hadPlantations, tobacco plantations]
-
A.
containsPlantation
chosen
Indicates that one entity includes or encompasses a plantation within its area, boundaries, or contents.
-
B.
isPlantation
Indicates that one entity is a large-scale agricultural estate or farm, typically used for cultivating cash crops, in relation to another entity.
-
C.
wasEnslavedIn
Indicates that an entity was held in a state of slavery within a specified place or context.
-
D.
ageWhenManagingPlantations
Indicates the age a person was when they were responsible for managing plantations.
-
E.
wasFormerlyEnslaved
Indicates that an entity was previously held in a condition of slavery or bondage but is no longer enslaved.
- 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_69f76e95fa40819091e14681087ae5e4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.