Triple
T20522368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saguenay, Quebec |
E503841
|
entity |
| Predicate | formedByMergerOf |
P77
|
FINISHED |
| Object | Jonquière |
—
|
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: Jonquière | Statement: [Saguenay, Quebec, formedByMergerOf, Jonquière]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonquière Context triple: [Saguenay, Quebec, formedByMergerOf, Jonquière]
-
A.
Jonquière
chosen
Jonquière is a former city in Quebec, Canada, now a borough of Saguenay, known historically for its industrial development and aluminum production.
-
B.
La Tuque
La Tuque is a city in the Mauricie region of Quebec, Canada, known for its vast forested territory and outdoor recreational activities.
-
C.
Repentigny
Repentigny is a suburban city in southwestern Quebec, Canada, located northeast of Montreal along the north shore of the Saint Lawrence River.
-
D.
Quesnel
Quesnel is a small city in central British Columbia, Canada, known historically as a Cariboo Gold Rush hub and a regional center for the forestry industry.
-
E.
Bois-Franc
Bois-Franc is a residential neighbourhood in the borough of Saint-Laurent in Montreal, Quebec, known for its planned community design and proximity to public transit.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f46488c819093687b4e07837793 |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.