Triple
T1058044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | P Street NW |
E22841
|
entity |
| Predicate | hasNeighborhoodCharacter |
P9356
|
FINISHED |
| Object | residential |
—
|
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: residential | Statement: [P Street NW, hasNeighborhoodCharacter, residential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighborhoodCharacter Context triple: [P Street NW, hasNeighborhoodCharacter, residential]
-
A.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
B.
neighborhoodCharacteristic
chosen
Indicates that a particular characteristic, feature, or quality is associated with or describes a given neighborhood.
-
C.
hasNeighborhoodAlong
Indicates that one entity has a neighboring area or region that extends along the boundary or length of another entity.
-
D.
hasSuburbanCharacter
Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
-
E.
hasNearbyCommunity
Indicates that one entity has another community located close to it in geographic or spatial terms.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4ba6e35ac8190802341c31bda0e3b |
completed | March 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69a4b7340a048190807363f19d17a58f |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.