Triple
T6925863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C Street SE |
E160305
|
entity |
| Predicate | zonedAreaType |
P36294
|
FINISHED |
| Object | mixed residential and institutional area |
—
|
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 residential and institutional area | Statement: [C Street SE, zonedAreaType, mixed residential and institutional area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zonedAreaType Context triple: [C Street SE, zonedAreaType, mixed residential and institutional area]
-
A.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
B.
zoneType
chosen
Indicates the classification or category of a zone that specifies its type or functional designation.
-
C.
typeOfAreaRepresented
Indicates that one entity specifies the kind or category of area that another entity represents.
-
D.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
E.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
- 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_69c6884d350081908d8a970e4d40ad78 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da1aa9c48190b63a04be2ed9e266 |
completed | March 27, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bb577c81908ee8b415b4281f3d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:27 p.m.