Triple
T12623876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sherbrooke |
E301459
|
entity |
| Predicate | populationRankInQuebec |
P105964
|
FINISHED |
| Object | sixth-largest city in Quebec |
—
|
LITERAL 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: sixth-largest city in Quebec | Statement: [Sherbrooke, populationRankInQuebec, sixth-largest city in Quebec]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: populationRankInQuebec Context triple: [Sherbrooke, populationRankInQuebec, sixth-largest city in Quebec]
-
A.
hasPopulationRankInCanada
Indicates the relative position of an entity’s population size compared to other entities within Canada.
-
B.
economicRankInCanada
Indicates the relative economic standing or ranking of an entity within the context of Canada’s economy.
-
C.
rankBySurfaceAreaInCanada
Indicates the relative ordering of entities based on the size of their surface area within the geographic boundaries of Canada.
-
D.
populationProvince
Indicates that a specified population figure is associated with, or belongs to, a particular province.
-
E.
populationRankInFrance
Indicates the relative position of an entity in an ordered list based on its population size within France.
- F. None of above. chosen
Provenance (4 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b195108190ac25bd95e644ace4 |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d96179c7648190a05a13991d62bebb |
completed | April 10, 2026, 8:45 p.m. |
Created at: April 9, 2026, 5:14 p.m.