Triple
T4996498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baie-D’Urfé |
E112258
|
entity |
| Predicate | hasNeighbour |
P5707
|
FINISHED |
| Object | Senneville |
E142719
|
NE 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: Senneville | Statement: [Baie-D’Urfé, hasNeighbour, Senneville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Senneville Context triple: [Baie-D’Urfé, hasNeighbour, 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.
Blainville
Blainville is a suburban town in southwestern Quebec, Canada, known for its residential communities and proximity to the Greater Montreal area.
-
C.
Villeneuve-le-Roi
Villeneuve-le-Roi is a suburban commune in the southeastern outskirts of Paris, France, situated along the Seine River and closely linked to the nearby Orly Airport.
-
D.
Limoilou
Limoilou is a primarily residential neighborhood in Quebec City, Canada, known for its dense urban fabric, vibrant local commerce, and historic working-class character.
-
E.
Val-Bélair
Val-Bélair is a suburban district of Quebec City, Quebec, known for its residential character and proximity to natural areas and military installations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd4432b32c81909f3b3c6bd10f0653 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd72a130708190b9bc1393ba78bfb1 |
completed | March 20, 2026, 4:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be8a3489f08190a338de8d8be09813 |
completed | March 21, 2026, 12:08 p.m. |
Created at: March 20, 2026, 1:34 p.m.