Triple
T2587146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novi, Michigan |
E58031
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Bob Gatt
Bob Gatt is an American local politician who has served as the mayor of Novi, Michigan.
|
E278769
|
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: Bob Gatt | Statement: [Novi, Michigan, hasMayor, Bob Gatt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bob Gatt Context triple: [Novi, Michigan, hasMayor, Bob Gatt]
-
A.
Don Granato
Don Granato is an American professional ice hockey coach known for leading the NHL’s Buffalo Sabres and for his extensive development work with young players.
-
B.
John Brancato
John Brancato is an American screenwriter best known for co-writing major Hollywood films such as "The Game," "Terminator 3: Rise of the Machines," and "Terminator Salvation."
-
C.
Bob Giusti
Bob Giusti is an artist known for creating cover artwork, including the cover for the novel "It."
-
D.
Tony DiCicco
Tony DiCicco was an American soccer coach best known for leading the U.S. women’s national team to victory in the 1996 Olympics and the 1999 FIFA Women’s World Cup.
-
E.
Ernie Sabella
Ernie Sabella is an American actor and voice actor best known for voicing the warthog Pumbaa in Disney’s The Lion King franchise.
- 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: Bob Gatt Triple: [Novi, Michigan, hasMayor, Bob Gatt]
Generated description
Bob Gatt is an American local politician who has served as the mayor of Novi, Michigan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bob Gatt Target entity description: Bob Gatt is an American local politician who has served as the mayor of Novi, Michigan.
-
A.
Don Granato
Don Granato is an American professional ice hockey coach known for leading the NHL’s Buffalo Sabres and for his extensive development work with young players.
-
B.
John Brancato
John Brancato is an American screenwriter best known for co-writing major Hollywood films such as "The Game," "Terminator 3: Rise of the Machines," and "Terminator Salvation."
-
C.
Bob Giusti
Bob Giusti is an artist known for creating cover artwork, including the cover for the novel "It."
-
D.
Tony DiCicco
Tony DiCicco was an American soccer coach best known for leading the U.S. women’s national team to victory in the 1996 Olympics and the 1999 FIFA Women’s World Cup.
-
E.
Ernie Sabella
Ernie Sabella is an American actor and voice actor best known for voicing the warthog Pumbaa in Disney’s The Lion King franchise.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd3f8a3888190889c537e6df07305 |
completed | March 7, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af65848e788190b2b01595540b1a10 |
completed | March 10, 2026, 12:27 a.m. |
| NEDg | Description generation | batch_69af6694dd248190ad6d579d504b5f27 |
completed | March 10, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af677577c88190be9a66fea85ab899 |
completed | March 10, 2026, 12:36 a.m. |
Created at: March 6, 2026, 9:49 p.m.