Triple
T32610065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portuguese Canadians |
E833629
|
entity |
| Predicate | concentratedNeighbourhood |
P70368
|
FINISHED |
| Object | Little Portugal, Toronto |
—
|
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: Little Portugal, Toronto | Statement: [Portuguese Canadians, concentratedNeighbourhood, Little Portugal, Toronto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concentratedNeighbourhood Context triple: [Portuguese Canadians, concentratedNeighbourhood, Little Portugal, Toronto]
-
A.
neighborhood
Indicates that one entity is located in close spatial proximity to another, typically within the same local area or district.
-
B.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
C.
concentratedInCity
Indicates that a large proportion or primary presence of something is located within a particular city.
-
D.
hasPopulationConcentrationIn
chosen
Indicates that a population is densely or significantly clustered within a specified geographic area or region.
-
E.
typicalNeighborhoods
Indicates that the associated neighborhoods are characteristic or commonly found examples for the given entity or 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
Created at: May 1, 2026, 1:06 a.m.