Triple
T22936653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreal Census Division |
E569603
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Senneville |
—
|
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: Senneville | Statement: [Montreal Census Division, contains, Senneville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senneville Context triple: [Montreal Census Division, contains, Senneville]
-
A.
Senneville
chosen
Senneville is a small, affluent suburban village located at the western tip of the Island of Montreal in Quebec, Canada.
-
B.
Ville-au-Bois
Ville-au-Bois is a small settlement located within the municipality of Stoumont in the province of Liège, Belgium.
-
C.
Émanville
Émanville is a small French commune located in northern France within the Eure department of the Normandy region.
-
D.
Blainville
Blainville was a French zoologist and anatomist known for his influential work in comparative anatomy and taxonomy in the early 19th century.
-
E.
Blainville
Blainville is a suburban town in southwestern Quebec, Canada, known for its residential communities and proximity to the Greater Montreal area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1813608e48190922df7a5386dc391 |
completed | April 29, 2026, 3:55 a.m. |
Created at: April 17, 2026, 3:45 p.m.