Triple
T19308114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Archbishop of Montreal |
E482894
|
entity |
| Predicate | currentHolder |
P8
|
FINISHED |
| Object | Christian Lépine |
—
|
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: Christian Lépine | Statement: [Metropolitan Archbishop of Montreal, currentHolder, Christian Lépine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christian Lépine Context triple: [Metropolitan Archbishop of Montreal, currentHolder, Christian Lépine]
-
A.
Christian Lépine
chosen
Christian Lépine is a Canadian Roman Catholic prelate who serves as the Archbishop of Montreal.
-
B.
Stanislas Lépine
Stanislas Lépine was a 19th-century French painter known for his quiet, atmospheric urban and river landscapes of Paris, often associated with the Impressionist movement.
-
C.
Marc Lépine
Marc Lépine was a Canadian mass murderer who killed 14 women in the 1989 antifeminist attack at Montreal’s École Polytechnique.
-
D.
Guy Gendron
Guy Gendron was a Canadian professional ice hockey left winger who played in the NHL during the 1950s and 1960s, notably with teams such as the New York Rangers and Boston Bruins.
-
E.
Jean Lépine
Jean Lépine is a cinematographer known for his work on the film "One Christmas."
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604cb47c88190bd01e6f5f4d2204f |
completed | April 20, 2026, 10:49 a.m. |
Created at: April 10, 2026, 1:32 p.m.