Triple
T13154678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montérégie |
E312551
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Beloeil |
E422452
|
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: Beloeil | Statement: [Montérégie, contains, Beloeil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beloeil Context triple: [Montérégie, contains, Beloeil]
-
A.
Beloeil
chosen
Beloeil is a suburban city in southwestern Quebec, Canada, located along the Richelieu River opposite Mont-Saint-Hilaire and forming part of the greater Montreal area.
-
B.
Valée
Valée is a French surname most notably borne by Sylvain Charles Valée, a 19th-century French military officer and Marshal of France.
-
C.
Gouin
Gouin is a French surname most notably associated with Félix Gouin, a mid-20th-century French socialist politician and former head of government.
-
D.
Bouchet
Bouchet is a surname most notably associated with Edward Alexander Bouchet, one of the first African Americans to earn a Ph.D. in the United States.
-
E.
Gouais
Gouais is an ancient white wine grape variety historically important as a parent of many classic European grape cultivars.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c06ccb881909390df18e1a6f7ed |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaee8aa0819089994b85d56c7740 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 9:11 p.m.