Triple
T9071664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinity Street, Hartford |
E217379
|
entity |
| Predicate | streetscapeContext |
P24448
|
FINISHED |
| Object | faces Bushnell Park |
—
|
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: faces Bushnell Park | Statement: [Trinity Street, Hartford, streetscapeContext, faces Bushnell Park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetscapeContext Context triple: [Trinity Street, Hartford, streetscapeContext, faces Bushnell Park]
-
A.
isPartOfStreetscape
Indicates that something forms a component or element within the overall layout or visual composition of a streetscape.
-
B.
cityScene
Indicates a scene or setting that takes place within an urban or city environment.
-
C.
urbanLayout
Indicates how the spatial arrangement, organization, and structure of buildings, streets, and public spaces relate to one another within an urban area.
-
D.
betweenStreets
Indicates that one location is situated between two specified streets, typically along a road segment bounded by those streets.
-
E.
hasStreetEnvironment
chosen
Indicates that an entity is associated with or characterized by a particular type or quality of street-level surroundings or conditions.
- 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_69ca83d6c14c8190bc056d927f00a2a2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc955ec5c0819089bb42448edf391e |
completed | April 1, 2026, 3:47 a.m. |
| PD | Predicate disambiguation | batch_69cc65f881248190bfd220bb28a9fb5f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:12 p.m.