Triple
T4926824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Laurent |
E110596
|
entity |
| Predicate | hasResidentialNeighborhoods |
P9064
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Saint-Laurent, hasResidentialNeighborhoods, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResidentialNeighborhoods Context triple: [Saint-Laurent, hasResidentialNeighborhoods, true]
-
A.
hasResidentialArea
chosen
Indicates that an entity includes, contains, or is associated with an area designated for people to live or reside.
-
B.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
-
C.
isResidentialTown
Indicates that a town is primarily used or designated for residential living rather than for commercial, industrial, or other primary purposes.
-
D.
isResidential
Indicates that something is used or designated primarily for people to live in, rather than for commercial, industrial, or other non-living purposes.
-
E.
isResidentialSuburbOf
Indicates that one area is a residential suburb that is part of or lies within the urban region of another area.
- 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_69bd4415190c8190817bee7ec9f9f944 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70354bd081909291a43439f42ed3 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3695c8819094e7ad2f6d4ba1ac |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:30 p.m.