Triple
T437452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgetown, Washington, D.C. |
E10040
|
entity |
| Predicate | zonedAs |
P727
|
FINISHED |
| Object | mixed-use neighborhood |
—
|
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: mixed-use neighborhood | Statement: [Georgetown, Washington, D.C., zonedAs, mixed-use neighborhood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zonedAs Context triple: [Georgetown, Washington, D.C., zonedAs, mixed-use neighborhood]
-
A.
zone
Indicates that an entity is located within, associated with, or assigned to a particular geographic or conceptual area or zone.
-
B.
hasZone
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
C.
zoningCharacter
chosen
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
-
D.
exampleZoneName
Indicates that an entity is associated with a zone identified by a specific example or placeholder name.
-
E.
locatedInTimeZone
Indicates that an entity exists or an event occurs within the temporal bounds defined by a specific time zone.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef26bb78819089b3b5dac0330619 |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddb98e081909efcf9f0a955a908 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.