Triple
T33907451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eliza Lucas Pinckney |
E869221
|
entity |
| Predicate | ageWhenManagingPlantations |
P177896
|
FINISHED |
| Object | about 16 |
—
|
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: about 16 | Statement: [Eliza Lucas Pinckney, ageWhenManagingPlantations, about 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageWhenManagingPlantations Context triple: [Eliza Lucas Pinckney, ageWhenManagingPlantations, about 16]
-
A.
containsPlantation
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.
numberOfEnslaved
Indicates the quantity of individuals who were held in a state of enslavement in relation to a given entity or context.
-
D.
plantedInCentury
Indicates that something was planted during a specified century.
-
E.
hadEstates
Indicates that an entity possessed or owned one or more estates (properties or landholdings).
- F. None of above. chosen
Provenance (4 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_69f3499869bc8190b6c33a81686af226 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7051ad6e4819095e82bbd64761803 |
completed | May 3, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69f700fe24e08190998e2c96fbaaad38 |
completed | May 3, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69f70519f114819080659840c04d7911 |
completed | May 3, 2026, 8:19 a.m. |
Created at: May 1, 2026, 1:48 a.m.