Triple
T32858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One First Street NE, Washington, D.C. |
E655
|
entity |
| Predicate | zoningContext |
P36
|
FINISHED |
| Object | federal government use |
—
|
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: federal government use | Statement: [One First Street NE, Washington, D.C., zoningContext, federal government use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zoningContext Context triple: [One First Street NE, Washington, D.C., zoningContext, federal government use]
-
A.
zoningCharacter
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
-
B.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
C.
context
chosen
Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
-
D.
locatedBetween
Indicates that one entity is positioned spatially between two other reference entities.
-
E.
areaServed
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2496ffc548190b545f998cbebd5b9 |
completed | Feb. 28, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69a248717f5081909952a8c9ed1e1742 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.