Triple
T13752062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blainville-Boisbriand Armada |
E330376
|
entity |
| Predicate | hasFanBaseIn |
P897
|
FINISHED |
| Object | Blainville |
E238268
|
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: Blainville | Statement: [Blainville-Boisbriand Armada, hasFanBaseIn, Blainville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blainville Context triple: [Blainville-Boisbriand Armada, hasFanBaseIn, Blainville]
-
A.
Blainville
Blainville was a French zoologist and anatomist known for his influential work in comparative anatomy and taxonomy in the early 19th century.
-
B.
Blainville
chosen
Blainville is a suburban town in southwestern Quebec, Canada, known for its residential communities and proximity to the Greater Montreal area.
-
C.
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.
-
D.
Senneville
Senneville is a small, affluent suburban village located at the western tip of the Island of Montreal in Quebec, Canada.
-
E.
Blainville-sur-l'Eau
Blainville-sur-l'Eau is a commune in northeastern France known for its location along the Meurthe River in the Meurthe-et-Moselle department.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0215cfa08190aaed8b089aff217b |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0ded1e0819097ef42533357caf8 |
completed | May 3, 2026, 9:40 p.m. |
Created at: April 9, 2026, 10:09 p.m.