Triple
T32609989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College Street Little Italy |
E833627
|
entity |
| Predicate | hasPrimaryCommercialStrip |
P30026
|
FINISHED |
| Object | College Street |
—
|
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: College Street | Statement: [College Street Little Italy, hasPrimaryCommercialStrip, College Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryCommercialStrip Context triple: [College Street Little Italy, hasPrimaryCommercialStrip, College Street]
-
A.
hasCommercialStrip
Indicates that an area or entity contains or is associated with a zone characterized by a concentration of commercial businesses or retail establishments.
-
B.
isPrimaryCommercialAreaOf
Indicates that one area serves as the main center of commercial activity for another specified place or region.
-
C.
isMajorCommercialStreetOf
Indicates that a street serves as a primary, heavily used route for commercial activity within a specified area or locality.
-
D.
hasMainStreet
Indicates that a place or locality possesses a primary street commonly recognized as its main thoroughfare.
-
E.
hasMajorRetailCorridor
chosen
Indicates that a place contains or is associated with a primary commercial street or area characterized by a high concentration of retail businesses.
- 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a00d508290081909f3d5dfbb2e80c8e |
completed | May 10, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_6a00d49da4cc81909566ad286ec22292 |
completed | May 10, 2026, 6:55 p.m. |
Created at: May 1, 2026, 1:06 a.m.