Triple
T3126431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nottz |
E65307
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object |
Asher Roth
Asher Roth is an American rapper best known for his 2009 hit single "I Love College" and his laid-back, college-themed lyrical style.
|
E330191
|
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: Asher Roth | Statement: [Nottz, associatedAct, Asher Roth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asher Roth Context triple: [Nottz, associatedAct, Asher Roth]
-
A.
Ashton Meem
Ashton Meem is an American woman best known as the first wife of NFL quarterback Russell Wilson and for her work in advertising and event planning.
-
B.
Mac Miller
Mac Miller was an American rapper, singer, and producer known for his introspective lyrics, evolving musical style, and influential presence in 2010s hip hop.
-
C.
Craig Bierko
Craig Bierko is an American actor known for his work in film, television, and theater, often playing charismatic or villainous roles.
-
D.
Cam Guthrie
Cam Guthrie is a Canadian politician best known as the long-serving mayor of the city of Guelph, Ontario.
-
E.
Matthew Maher
Matthew Maher is an American character actor known for his offbeat supporting roles in independent films, theater, and television.
- 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: Asher Roth Triple: [Nottz, associatedAct, Asher Roth]
Generated description
Asher Roth is an American rapper best known for his 2009 hit single "I Love College" and his laid-back, college-themed lyrical style.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Asher Roth Target entity description: Asher Roth is an American rapper best known for his 2009 hit single "I Love College" and his laid-back, college-themed lyrical style.
-
A.
Ashton Meem
Ashton Meem is an American woman best known as the first wife of NFL quarterback Russell Wilson and for her work in advertising and event planning.
-
B.
Mac Miller
Mac Miller was an American rapper, singer, and producer known for his introspective lyrics, evolving musical style, and influential presence in 2010s hip hop.
-
C.
Craig Bierko
Craig Bierko is an American actor known for his work in film, television, and theater, often playing charismatic or villainous roles.
-
D.
Cam Guthrie
Cam Guthrie is a Canadian politician best known as the long-serving mayor of the city of Guelph, Ontario.
-
E.
Matthew Maher
Matthew Maher is an American character actor known for his offbeat supporting roles in independent films, theater, and television.
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada544cb648190b5ed430dbd561d52 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f7926248190b8f08e3a626e8eab |
completed | March 12, 2026, 12:57 a.m. |
| NEDg | Description generation | batch_69b2135f05c88190b926556828a038ac |
completed | March 12, 2026, 1:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b214268d588190996d909297baaffc |
completed | March 12, 2026, 1:17 a.m. |
Created at: March 8, 2026, 3:04 p.m.