Triple
T7068317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadlands |
E164617
|
entity |
| Predicate | nearEconomicArea |
P71206
|
FINISHED |
| Object | data centers in Loudoun County |
—
|
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: data centers in Loudoun County | Statement: [Broadlands, nearEconomicArea, data centers in Loudoun County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearEconomicArea Context triple: [Broadlands, nearEconomicArea, data centers in Loudoun County]
-
A.
hasNearbyEconomicRegion
Indicates that one economic region is geographically close to or adjacent to another economic region.
-
B.
nearbyEconomicActivity
chosen
Indicates that there is economic activity occurring in close physical proximity to the referenced entity.
-
C.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
E.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4a935488190a8c9c21bf30dd5d4 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bdc1f08190975fcdbbb1854d1e |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:39 p.m.