Triple
T8149239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Clair Avenue West |
E190291
|
entity |
| Predicate | hasCommercialCharacter |
P23616
|
FINISHED |
| Object | streetfront retail |
—
|
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: streetfront retail | Statement: [St. Clair Avenue West, hasCommercialCharacter, streetfront retail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialCharacter Context triple: [St. Clair Avenue West, hasCommercialCharacter, streetfront retail]
-
A.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
B.
hasCommercialFunction
chosen
Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
-
C.
commercialCharacter
Indicates that an entity is a fictional or stylized persona used in a commercial or advertising context.
-
D.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
E.
hasLanguageCharacter
Indicates that an entity uses, contains, or is associated with a specific written or symbolic character from a language.
- 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb447fc4308190b9436b0fe51a70a5 |
completed | March 31, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cb36a0847c8190af9038aef78319b3 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:37 p.m.