Triple
T3126886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Bhasker |
E65317
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object |
Fun.
Fun. is an American indie pop band best known for their anthemic hit singles like "We Are Young" and "Some Nights."
|
E330219
|
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: Fun. | Statement: [Jeff Bhasker, workedWith, Fun.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fun. Context triple: [Jeff Bhasker, workedWith, Fun.]
-
A.
Just for Fun
"Just for Fun" is a song from Beyoncé’s genre-blending 2024 album *Cowboy Carter*, which explores country, Americana, and Black Southern musical traditions.
-
B.
The Fun of It
The Fun of It is a 1932 memoir by pioneering aviator Amelia Earhart, recounting her experiences in early aviation and encouraging women to pursue flying.
-
C.
The Lot of Fun
The Lot of Fun is the famous nickname for Hal Roach Studios, the prolific Hollywood studio best known for producing classic comedy films and series such as Laurel and Hardy and Our Gang.
-
D.
Fort Fun
Fort Fun is a playful nickname for Fort Collins, Colorado, highlighting the city’s lively, recreation-focused atmosphere.
-
E.
Pleasure
Pleasure is a 1985 Italian erotic drama film directed by Joe D'Amato that explores themes of desire, fantasy, and sexual liberation.
- 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: Fun. Triple: [Jeff Bhasker, workedWith, Fun.]
Generated description
Fun. is an American indie pop band best known for their anthemic hit singles like "We Are Young" and "Some Nights."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fun. Target entity description: Fun. is an American indie pop band best known for their anthemic hit singles like "We Are Young" and "Some Nights."
-
A.
Just for Fun
"Just for Fun" is a song from Beyoncé’s genre-blending 2024 album *Cowboy Carter*, which explores country, Americana, and Black Southern musical traditions.
-
B.
The Fun of It
The Fun of It is a 1932 memoir by pioneering aviator Amelia Earhart, recounting her experiences in early aviation and encouraging women to pursue flying.
-
C.
The Lot of Fun
The Lot of Fun is the famous nickname for Hal Roach Studios, the prolific Hollywood studio best known for producing classic comedy films and series such as Laurel and Hardy and Our Gang.
-
D.
Fort Fun
Fort Fun is a playful nickname for Fort Collins, Colorado, highlighting the city’s lively, recreation-focused atmosphere.
-
E.
Pleasure
Pleasure is a 1985 Italian erotic drama film directed by Joe D'Amato that explores themes of desire, fantasy, and sexual liberation.
- 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.