Triple
T13516141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In the Cut |
E322763
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Yvonne Jung
Yvonne Jung is an American actress known for her work in film and television, including roles in crime dramas and independent movies.
|
E1044821
|
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: Yvonne Jung | Statement: [In the Cut, castMember, Yvonne Jung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yvonne Jung Context triple: [In the Cut, castMember, Yvonne Jung]
-
A.
Yvonne Eckert
Yvonne Eckert is a notable individual recognized as a prominent bearer of the surname Eckert.
-
B.
Brigitte Lin
Brigitte Lin is a celebrated Taiwanese actress best known internationally for her iconic roles in 1980s–1990s Hong Kong cinema, including acclaimed collaborations with auteur directors such as Wong Kar-wai.
-
C.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
D.
Odette Yustman
Odette Yustman is an American actress known for her roles in films such as Cloverfield and The Unborn, as well as various television series.
-
E.
Ursula Yovich
Ursula Yovich is an Australian Indigenous actress, singer, and playwright known for her acclaimed work in theatre, film, 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: Yvonne Jung Triple: [In the Cut, castMember, Yvonne Jung]
Generated description
Yvonne Jung is an American actress known for her work in film and television, including roles in crime dramas and independent movies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yvonne Jung Target entity description: Yvonne Jung is an American actress known for her work in film and television, including roles in crime dramas and independent movies.
-
A.
Yvonne Eckert
Yvonne Eckert is a notable individual recognized as a prominent bearer of the surname Eckert.
-
B.
Brigitte Lin
Brigitte Lin is a celebrated Taiwanese actress best known internationally for her iconic roles in 1980s–1990s Hong Kong cinema, including acclaimed collaborations with auteur directors such as Wong Kar-wai.
-
C.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
D.
Odette Yustman
Odette Yustman is an American actress known for her roles in films such as Cloverfield and The Unborn, as well as various television series.
-
E.
Ursula Yovich
Ursula Yovich is an Australian Indigenous actress, singer, and playwright known for her acclaimed work in theatre, film, 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa0ed508190b2855171b1945e84 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75496496c819093a9e763d293bcf7 |
completed | May 3, 2026, 1:58 p.m. |
| NEDg | Description generation | batch_69f75619ab7081909ca0c113d9ea349e |
completed | May 3, 2026, 2:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7569429348190b6b1b901d5481921 |
completed | May 3, 2026, 2:07 p.m. |
Created at: April 9, 2026, 9:44 p.m.