Triple
T1642562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bryan Trottier |
E35505
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Trottier
Trottier is a surname most prominently associated with Bryan Trottier, a Hall of Fame Canadian-American ice hockey player and multiple Stanley Cup champion.
|
E186600
|
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: Trottier | Statement: [Bryan Trottier, familyName, Trottier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trottier Context triple: [Bryan Trottier, familyName, Trottier]
-
A.
Virage Chatillon
Virage Chatillon is a French youth football club known for being one of the early teams in Thierry Henry’s development.
-
B.
Stoffels
Stoffels is the surname of Hendrickje Stoffels, best known as the partner and model of the Dutch painter Rembrandt van Rijn.
-
C.
Gaston Chevrolet
Gaston Chevrolet was a Swiss-American race car driver and automotive figure, known as the younger brother of Louis Chevrolet and for his involvement in early American motor racing.
-
D.
Traton
Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
-
E.
Suter
Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
- 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: Trottier Triple: [Bryan Trottier, familyName, Trottier]
Generated description
Trottier is a surname most prominently associated with Bryan Trottier, a Hall of Fame Canadian-American ice hockey player and multiple Stanley Cup champion.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trottier Target entity description: Trottier is a surname most prominently associated with Bryan Trottier, a Hall of Fame Canadian-American ice hockey player and multiple Stanley Cup champion.
-
A.
Virage Chatillon
Virage Chatillon is a French youth football club known for being one of the early teams in Thierry Henry’s development.
-
B.
Stoffels
Stoffels is the surname of Hendrickje Stoffels, best known as the partner and model of the Dutch painter Rembrandt van Rijn.
-
C.
Gaston Chevrolet
Gaston Chevrolet was a Swiss-American race car driver and automotive figure, known as the younger brother of Louis Chevrolet and for his involvement in early American motor racing.
-
D.
Traton
Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
-
E.
Suter
Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a3f4d8c8190aa0a44d1c9b1a7f0 |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad60a0096c81909dc723d0db95481e |
completed | March 8, 2026, 11:42 a.m. |
| NEDg | Description generation | batch_69ad620fe35481909bf4751001e29161 |
completed | March 8, 2026, 11:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad626d42388190b6a961a84333bd21 |
completed | March 8, 2026, 11:50 a.m. |
Created at: March 4, 2026, 7:28 p.m.