Triple
T6484050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Street (Alexandria, Virginia) |
E146463
|
entity |
| Predicate | streetscapeCharacter |
P28273
|
FINISHED |
| Object | historic and pedestrian-oriented |
—
|
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: historic and pedestrian-oriented | Statement: [King Street (Alexandria, Virginia), streetscapeCharacter, historic and pedestrian-oriented]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetscapeCharacter Context triple: [King Street (Alexandria, Virginia), streetscapeCharacter, historic and pedestrian-oriented]
-
A.
isPartOfStreetscape
Indicates that something forms a component or element within the overall layout or visual composition of a streetscape.
-
B.
hasPedestrianCharacter
chosen
Indicates that something possesses qualities, features, or behavior characteristic of pedestrians or pedestrian use.
-
C.
cycleCharacter
Indicates that one character in a sequence is followed by another in a repeating (cyclic) order.
-
D.
neighborCharacter
Indicates that one character is located adjacent to or next to another character in a given context.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
- 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a6de31c81909dd99d105f5bb4c2 |
completed | March 22, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:52 p.m.