Triple
T19770448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saputo Inc. |
E474869
|
entity |
| Predicate | locationCity |
P3207
|
FINISHED |
| Object | Montreal |
—
|
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: Montreal | Statement: [Saputo Inc., locationCity, Montreal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montreal Context triple: [Saputo Inc., locationCity, Montreal]
-
A.
Montreal
chosen
Montreal is the largest city in Quebec, Canada, known for its vibrant bilingual culture, historic architecture, and status as a major economic and cultural center.
-
B.
Montreal
Montreal was a prominent Crusader-era fortress in the Lordship of Oultrejordain, strategically controlling key trade and pilgrimage routes east of the Jordan River.
-
C.
Montreal
"Montreal" is a song by the American metal band Ataxia.
-
D.
Quebec City
Quebec City is the historic capital of the Canadian province of Quebec, renowned for its well-preserved fortified old town and rich French colonial heritage.
-
E.
Joliette
Joliette is a Montreal Metro station on the Green Line serving the Mercier–Hochelaga-Maisonneuve borough in Montreal, Quebec, Canada.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6535ab298819085263dc37cc898cb |
completed | April 20, 2026, 4:24 p.m. |
Created at: April 10, 2026, 1:48 p.m.