Triple
T33898285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loudoun County, Colony of Virginia |
E868974
|
entity |
| Predicate | hadSettlementPattern |
P1830
|
FINISHED |
| Object | rural 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: rural plantations | Statement: [Loudoun County, Colony of Virginia, hadSettlementPattern, rural plantations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadSettlementPattern Context triple: [Loudoun County, Colony of Virginia, hadSettlementPattern, rural plantations]
-
A.
hadSettlementFeature
Indicates that a settlement possessed or contained a particular physical or infrastructural feature.
-
B.
hadPrimarySettlementPattern
chosen
Indicates that an entity exhibited or was characterized by a particular dominant form or arrangement of human settlement.
-
C.
settlementPattern
Indicates how human dwellings or communities are spatially arranged and distributed across a geographic area.
-
D.
hasHumanSettlement
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
E.
settledAs
Indicates that one entity has been resolved, finalized, or agreed upon in the form or status of another entity.
- 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_69f34997703c8190866b1d404bce531f |
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. |
Created at: May 1, 2026, 1:48 a.m.