Triple
T8171441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Park View |
E190829
|
entity |
| Predicate | hasNearbyCorridor |
P29183
|
FINISHED |
| Object | Georgia Avenue NW commercial corridor |
—
|
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: Georgia Avenue NW commercial corridor | Statement: [Park View, hasNearbyCorridor, Georgia Avenue NW commercial corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCorridor Context triple: [Park View, hasNearbyCorridor, Georgia Avenue NW commercial corridor]
-
A.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
B.
nearbyConnectionViaPassageways
chosen
Indicates that two locations are close to each other and are connected specifically through one or more passageways.
-
C.
nearestEntrance
Indicates that one entrance is the closest access point to a given location or entity compared to all other possible entrances.
-
D.
hasNearbyCrossingPoint
Indicates that one location has a crossing point (such as a bridge, crosswalk, or intersection) situated close to it.
-
E.
hasServiceOnCorridor
Indicates that a service operates along, or is provided on, a specific corridor or route.
- 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_69ca82c1c0a08190bf8692b4d91a03ca |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb48056d0c819094575090a41e0083 |
completed | March 31, 2026, 4:05 a.m. |
| PD | Predicate disambiguation | batch_69cb36a4c40c81909f60aef0e1624c13 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:39 p.m.