Triple
T3208849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Sainte-Foy |
E67228
|
entity |
| Predicate | FrenchSide |
P46193
|
FINISHED |
| Object | included regular French troops and Canadian militia |
—
|
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: included regular French troops and Canadian militia | Statement: [Battle of Sainte-Foy, FrenchSide, included regular French troops and Canadian militia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrenchSide Context triple: [Battle of Sainte-Foy, FrenchSide, included regular French troops and Canadian militia]
-
A.
FrenchFlagship
Indicates that an entity serves as the primary or leading representative (flagship) of France in a given domain or context.
-
B.
situatedOnSideOf
Indicates that one entity is located along or beside the lateral part or edge of another entity.
-
C.
side2
Indicates that an entity is positioned on, associated with, or corresponds to the second side of another entity or structure.
-
D.
A-sideOf
Indicates that one entity is located on or corresponds to the A-side (first or primary side) of another entity, typically in a two-sided context.
-
E.
borderTownOnFrenchSide
Indicates that a town is located on the French side of a border shared with another country.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaa59888481908bdaefa1968d7f04 |
completed | March 8, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69ad9e078f7c8190813d9fcb4f5071fb |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f9259c8190afbc5ad0fa55436b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:07 p.m.