Triple
T20045524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rene Gagnon |
E497547
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Gagnon
Gagnon is a common French-origin surname, particularly prevalent in French-speaking regions such as Quebec, Canada.
|
E1409163
|
NE FINISHED |
How this triple was built (4 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: Gagnon | Statement: [Rene Gagnon, familyName, Gagnon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gagnon Context triple: [Rene Gagnon, familyName, Gagnon]
-
A.
Garron
Garron is a charming yet unscrupulous conman from the Doctor Who serial "The Ribos Operation," known for orchestrating elaborate planetary fraud schemes.
-
B.
Ghislain
Ghislain is a given name of French origin, used for both males and females and derived from the medieval name Ghislaine.
-
C.
Tremblay
Tremblay is a common French-Canadian surname, particularly prevalent in Quebec and associated with numerous public figures in sports, politics, and the arts.
-
D.
Grenier
Grenier is a French-origin surname borne by various notable individuals in fields such as acting, politics, and the arts.
-
E.
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gagnon Triple: [Rene Gagnon, familyName, Gagnon]
Generated description
Gagnon is a common French-origin surname, particularly prevalent in French-speaking regions such as Quebec, Canada.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gagnon Target entity description: Gagnon is a common French-origin surname, particularly prevalent in French-speaking regions such as Quebec, Canada.
-
A.
Garron
Garron is a charming yet unscrupulous conman from the Doctor Who serial "The Ribos Operation," known for orchestrating elaborate planetary fraud schemes.
-
B.
Ghislain
Ghislain is a given name of French origin, used for both males and females and derived from the medieval name Ghislaine.
-
C.
Tremblay
Tremblay is a common French-Canadian surname, particularly prevalent in Quebec and associated with numerous public figures in sports, politics, and the arts.
-
D.
Grenier
Grenier is a French-origin surname borne by various notable individuals in fields such as acting, politics, and the arts.
-
E.
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.
- F. None of above. chosen
Provenance (5 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632a5e888190ade41657ffd057f6 |
completed | April 20, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a081603b36c8190b82688c3235fc794 |
completed | May 16, 2026, 7 a.m. |
| NEDg | Description generation | batch_6a08180e5e988190a846aef83802cfc3 |
completed | May 16, 2026, 7:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0818970bb081908093589df4fc65b6 |
completed | May 16, 2026, 7:11 a.m. |
Created at: April 11, 2026, 3:37 p.m.