Triple
T16982115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terrebonne |
E411969
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Mathieu Traversy
Mathieu Traversy is a Canadian politician who serves as the mayor of Terrebonne, Quebec.
|
E1243218
|
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: Mathieu Traversy | Statement: [Terrebonne, hasMayor, Mathieu Traversy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mathieu Traversy Context triple: [Terrebonne, hasMayor, Mathieu Traversy]
-
A.
Trevor Yorke
Trevor Yorke is an author and illustrator known for his accessible books on British architecture, historic buildings, and period house styles.
-
B.
Travis Banton
Travis Banton was a prominent American Hollywood costume designer best known for his glamorous, influential work at Paramount Pictures during the 1920s and 1930s.
-
C.
Daniel Lapaine
Daniel Lapaine is an Australian actor known for his roles in films such as "Muriel's Wedding" and appearances in television series including "Black Mirror."
-
D.
Tyler Micoleau
Tyler Micoleau is an acclaimed American theatrical lighting designer known for his work on numerous stage productions, including the Broadway musical "The Band’s Visit."
-
E.
Trevor LeBlanc
Trevor LeBlanc is a fictional U.S. Army soldier and central character on the television drama series "Army Wives."
- 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: Mathieu Traversy Triple: [Terrebonne, hasMayor, Mathieu Traversy]
Generated description
Mathieu Traversy is a Canadian politician who serves as the mayor of Terrebonne, Quebec.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mathieu Traversy Target entity description: Mathieu Traversy is a Canadian politician who serves as the mayor of Terrebonne, Quebec.
-
A.
Trevor Yorke
Trevor Yorke is an author and illustrator known for his accessible books on British architecture, historic buildings, and period house styles.
-
B.
Travis Banton
Travis Banton was a prominent American Hollywood costume designer best known for his glamorous, influential work at Paramount Pictures during the 1920s and 1930s.
-
C.
Daniel Lapaine
Daniel Lapaine is an Australian actor known for his roles in films such as "Muriel's Wedding" and appearances in television series including "Black Mirror."
-
D.
Tyler Micoleau
Tyler Micoleau is an acclaimed American theatrical lighting designer known for his work on numerous stage productions, including the Broadway musical "The Band’s Visit."
-
E.
Trevor LeBlanc
Trevor LeBlanc is a fictional U.S. Army soldier and central character on the television drama series "Army Wives."
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d18830ac8190a20c89a87379ae94 |
completed | April 18, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d479610c8190a6281e6d4959b820 |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d503f4f08190a0dcdb050d5bc7a3 |
completed | May 10, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d5adee908190a13bfc765e7c8f06 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:32 a.m.