Triple
T10070155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanover County, Colony of Virginia |
E213599
|
entity |
| Predicate | secondaryCrops |
P65738
|
FINISHED |
| Object | corn |
—
|
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: corn | Statement: [Hanover County, Colony of Virginia, secondaryCrops, corn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryCrops Context triple: [Hanover County, Colony of Virginia, secondaryCrops, corn]
-
A.
secondaryFood
Indicates that one entity serves as a secondary or supplementary food source in relation to another entity.
-
B.
majorCrop
Indicates that a particular crop is one of the primary or most important crops cultivated in a given area or context.
-
C.
secondaryProducts
chosen
Indicates that certain entities arise as secondary or byproduct outputs from a primary process, activity, or production.
-
D.
cultivatedSpecies
Indicates that one entity is a species that is intentionally grown or cultivated by another entity.
-
E.
crop
Indicates the action of cutting or trimming part of an object or image, typically to remove unwanted outer areas while keeping a selected region.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcffa045c8190a08db0bb74cb006a |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b92573481909389bc6148ae7ea8 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:58 p.m.