Triple
T940093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Island of Montreal |
E20285
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Saint-Laurent
Saint-Laurent is a borough of Montreal known as a major residential and industrial hub on the Island of Montreal in Quebec, Canada.
|
E110596
|
NE FINISHED |
How this triple was built (4 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: Saint-Laurent | Statement: [Island of Montreal, contains, Saint-Laurent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Laurent Context triple: [Island of Montreal, contains, Saint-Laurent]
-
A.
Boncourt
Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
-
B.
de Chomedey
de Chomedey is the family name of Paul de Chomedey, Sieur de Maisonneuve, the French military officer and founder of Montreal.
-
C.
Saint-Cloud
Saint-Cloud is a commune just west of Paris, historically notable as the site where Napoleon Bonaparte staged the Coup of 18 Brumaire that ended the French Directory and ushered in his rule.
-
D.
Bernardin
Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
-
E.
Sorel
Sorel is a footwear and outerwear brand best known for its durable, stylish winter boots and cold-weather gear.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Saint-Laurent Triple: [Island of Montreal, contains, Saint-Laurent]
Generated description
Saint-Laurent is a borough of Montreal known as a major residential and industrial hub on the Island of Montreal in Quebec, Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saint-Laurent Target entity description: Saint-Laurent is a borough of Montreal known as a major residential and industrial hub on the Island of Montreal in Quebec, Canada.
-
A.
Boncourt
Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
-
B.
de Chomedey
de Chomedey is the family name of Paul de Chomedey, Sieur de Maisonneuve, the French military officer and founder of Montreal.
-
C.
Saint-Cloud
Saint-Cloud is a commune just west of Paris, historically notable as the site where Napoleon Bonaparte staged the Coup of 18 Brumaire that ended the French Directory and ushered in his rule.
-
D.
Bernardin
Bernardin is a well-known brand specializing in home canning and preserving supplies, particularly mason jars, lids, and related accessories.
-
E.
Sorel
Sorel is a footwear and outerwear brand best known for its durable, stylish winter boots and cold-weather gear.
- F. None of above. chosen
Provenance (5 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b38b7da08190ac0853655dab678a |
completed | March 1, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a826e30c448190acc1457a63d27a4a |
completed | March 4, 2026, 12:34 p.m. |
| NEDg | Description generation | batch_69a8343e16908190af102cfce025c31f |
completed | March 4, 2026, 1:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a834f3a9288190a8cd28165379cec6 |
completed | March 4, 2026, 1:34 p.m. |
Created at: March 1, 2026, 7:40 p.m.