Triple
T34206522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Community College of Philadelphia |
E877524
|
entity |
| Predicate | streetProximity |
P53174
|
FINISHED |
| Object | near 17th Street |
—
|
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: near 17th Street | Statement: [Community College of Philadelphia, streetProximity, near 17th Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetProximity Context triple: [Community College of Philadelphia, streetProximity, near 17th Street]
-
A.
proximityToLandmark
chosen
Indicates a spatial relationship where one entity is located near or close to a specified landmark.
-
B.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
C.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
-
D.
hasTransportationProximityTo
Indicates that one entity is located near or conveniently accessible to another entity in terms of transportation options or routes.
-
E.
nearbyCurrent
Indicates that one entity is located close to another entity at the present moment or in the current 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_69f349aff5f0819096275315abea5344 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7105085fc81909ece409d01619f82 |
completed | May 3, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:55 a.m.