Triple
T9854046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breakfast of Champions |
E239539
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Suzy Elmiger
Suzy Elmiger is a film editor known for her work on projects such as the adaptation of Kurt Vonnegut’s "Breakfast of Champions."
|
E825075
|
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: Suzy Elmiger | Statement: [Breakfast of Champions, editedBy, Suzy Elmiger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suzy Elmiger Context triple: [Breakfast of Champions, editedBy, Suzy Elmiger]
-
A.
Suzy Berhow
Suzy Berhow is an American animator, artist, and YouTube personality best known for her work on Game Grumps–related content and her own channels, such as KittyKatGaming.
-
B.
Jessica Szohr
Jessica Szohr is an American actress best known for her role as Vanessa Abrams on the television series "Gossip Girl" and later as a main cast member on the sci-fi comedy-drama "The Orville."
-
C.
Tania Nehme
Tania Nehme is an Australian film editor known for her work on acclaimed films such as the Indigenous Australian feature "Ten Canoes."
-
D.
Leila Behrens
Leila Behrens is a notable individual who bears the surname Behrens.
-
E.
Lila Yacoub
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
- 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: Suzy Elmiger Triple: [Breakfast of Champions, editedBy, Suzy Elmiger]
Generated description
Suzy Elmiger is a film editor known for her work on projects such as the adaptation of Kurt Vonnegut’s "Breakfast of Champions."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Suzy Elmiger Target entity description: Suzy Elmiger is a film editor known for her work on projects such as the adaptation of Kurt Vonnegut’s "Breakfast of Champions."
-
A.
Suzy Berhow
Suzy Berhow is an American animator, artist, and YouTube personality best known for her work on Game Grumps–related content and her own channels, such as KittyKatGaming.
-
B.
Jessica Szohr
Jessica Szohr is an American actress best known for her role as Vanessa Abrams on the television series "Gossip Girl" and later as a main cast member on the sci-fi comedy-drama "The Orville."
-
C.
Tania Nehme
Tania Nehme is an Australian film editor known for her work on acclaimed films such as the Indigenous Australian feature "Ten Canoes."
-
D.
Leila Behrens
Leila Behrens is a notable individual who bears the surname Behrens.
-
E.
Lila Yacoub
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
- 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_69ca84e4fdc08190a624425bcef98665 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb376d32c819089381cf6ed83629d |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5f21a04819099f23ede55ec3417 |
completed | April 5, 2026, 3:24 a.m. |
| NEDg | Description generation | batch_69d1d7a6a87c81908dcd79c776bb19a1 |
completed | April 5, 2026, 3:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d82007088190ac372c67a6760e65 |
completed | April 5, 2026, 3:33 a.m. |
Created at: March 30, 2026, 8:34 p.m.