Triple
T8829199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Square (Cleveland) |
E210089
|
entity |
| Predicate | hasStreetBounding |
P959
|
FINISHED |
| Object | Superior Avenue |
—
|
NE NERFINISHED |
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: Superior Avenue | Statement: [Public Square (Cleveland), hasStreetBounding, Superior Avenue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetBounding Context triple: [Public Square (Cleveland), hasStreetBounding, Superior Avenue]
-
A.
hasRoadBoundary
Indicates that a road segment is associated with a specific boundary or edge that defines its lateral limits.
-
B.
hasStreetLevel
Indicates that something is located at, accessible from, or directly associated with the street level of a building or area.
-
C.
hasStreet
chosen
Indicates that an entity is located on, associated with, or identified by a particular street.
-
D.
hasNearbyStreet
Indicates that one entity is located close to or adjacent to a street.
-
E.
hasConnectingStreet
Indicates that two locations are linked by a street that directly connects them.
- 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc604c52a48190807e46c15e3c1558 |
completed | April 1, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69cc5c23d08481908d8c9b0ad3d1dc00 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:47 p.m.