Triple
T1245756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Waterloo |
E26761
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
Gerald Hagey
Gerald Hagey was a Canadian academic and administrator best known as the founding president who led the development of the University of Waterloo into a major institution.
|
E151464
|
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: Gerald Hagey | Statement: [University of Waterloo, foundedBy, Gerald Hagey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerald Hagey Context triple: [University of Waterloo, foundedBy, Gerald Hagey]
-
A.
Tedd Munchak
Tedd Munchak was an American businessman best known for owning the Carolina Cougars franchise in the former American Basketball Association.
-
B.
Larry Daley
Larry Daley is the bumbling yet good-hearted night guard protagonist of the "Night at the Museum" film series, known for dealing with museum exhibits that magically come to life.
-
C.
Jim Harris
Jim Harris is a technology executive best known as one of the founders of the computer company Compaq.
-
D.
Frank Richard Wells
Frank Richard Wells was a son of the famed English writer H. G. Wells.
-
E.
Mike Gartner
Mike Gartner is a Canadian Hall of Fame right winger renowned as one of the NHL’s most prolific goal scorers, surpassing 700 career goals over a 19-season career.
- 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: Gerald Hagey Triple: [University of Waterloo, foundedBy, Gerald Hagey]
Generated description
Gerald Hagey was a Canadian academic and administrator best known as the founding president who led the development of the University of Waterloo into a major institution.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gerald Hagey Target entity description: Gerald Hagey was a Canadian academic and administrator best known as the founding president who led the development of the University of Waterloo into a major institution.
-
A.
Tedd Munchak
Tedd Munchak was an American businessman best known for owning the Carolina Cougars franchise in the former American Basketball Association.
-
B.
Larry Daley
Larry Daley is the bumbling yet good-hearted night guard protagonist of the "Night at the Museum" film series, known for dealing with museum exhibits that magically come to life.
-
C.
Jim Harris
Jim Harris is a technology executive best known as one of the founders of the computer company Compaq.
-
D.
Frank Richard Wells
Frank Richard Wells was a son of the famed English writer H. G. Wells.
-
E.
Mike Gartner
Mike Gartner is a Canadian Hall of Fame right winger renowned as one of the NHL’s most prolific goal scorers, surpassing 700 career goals over a 19-season career.
- 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf65c41c8190b4c65e015d1264c0 |
completed | March 1, 2026, 10:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbf1c90608190a0fa4d3722897966 |
completed | March 8, 2026, 12:13 a.m. |
| NEDg | Description generation | batch_69acbfc03f20819089a025fc745c9203 |
completed | March 8, 2026, 12:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acc0282080819087676813c2852a96 |
completed | March 8, 2026, 12:17 a.m. |
Created at: March 1, 2026, 7:47 p.m.