Triple
T4604988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College Park Historic District |
E100409
|
entity |
| Predicate | landscapeFeatures |
P22129
|
FINISHED |
| Object | front yards with setbacks |
—
|
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: front yards with setbacks | Statement: [College Park Historic District, landscapeFeatures, front yards with setbacks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landscapeFeatures Context triple: [College Park Historic District, landscapeFeatures, front yards with setbacks]
-
A.
landscapeType
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
B.
terrainFeature
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
C.
hasLandscapeFeatures
chosen
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
D.
landscapeElement
Indicates that one entity functions as a landscape-related feature or component in relation to another entity.
-
E.
geographicalNature
Indicates the natural geographic characteristics or physical landscape type associated with a place or region.
- 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_69bd43cce1e08190a07d53af6a9b6c24 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5999f9c88190a43309573df61159 |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522e2d5c8190937d0b5574f78f99 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:12 p.m.