Triple
T8766596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logan Lucky |
E208352
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Mellie Logan
Mellie Logan is a sharp-witted, resourceful sister in the film "Logan Lucky," known for her crucial role in helping execute the heist.
|
E757313
|
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: Mellie Logan | Statement: [Logan Lucky, mainCharacter, Mellie Logan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mellie Logan Context triple: [Logan Lucky, mainCharacter, Mellie Logan]
-
A.
Jacqueline Logan
Jacqueline Logan was an American silent film actress best known for her prominent roles in 1920s Hollywood cinema.
-
B.
Laura Lyons
Laura Lyons is the mother of American fashion model Lily Aldridge.
-
C.
Joan Holloway
Joan Holloway is a poised and ambitious office manager-turned-partner at a 1960s New York advertising agency in the television series "Mad Men," known for her sharp wit, competence, and complex personal life.
-
D.
Kate Pearson
Kate Pearson is a central character in the television drama "This Is Us," known for her emotional journey dealing with family dynamics, body image, and personal growth.
-
E.
Fortune Feimster
Fortune Feimster is an American stand-up comedian, writer, and actress known for her self-deprecating humor and roles in television and film comedies.
- 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: Mellie Logan Triple: [Logan Lucky, mainCharacter, Mellie Logan]
Generated description
Mellie Logan is a sharp-witted, resourceful sister in the film "Logan Lucky," known for her crucial role in helping execute the heist.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mellie Logan Target entity description: Mellie Logan is a sharp-witted, resourceful sister in the film "Logan Lucky," known for her crucial role in helping execute the heist.
-
A.
Jacqueline Logan
Jacqueline Logan was an American silent film actress best known for her prominent roles in 1920s Hollywood cinema.
-
B.
Laura Lyons
Laura Lyons is the mother of American fashion model Lily Aldridge.
-
C.
Joan Holloway
Joan Holloway is a poised and ambitious office manager-turned-partner at a 1960s New York advertising agency in the television series "Mad Men," known for her sharp wit, competence, and complex personal life.
-
D.
Kate Pearson
Kate Pearson is a central character in the television drama "This Is Us," known for her emotional journey dealing with family dynamics, body image, and personal growth.
-
E.
Fortune Feimster
Fortune Feimster is an American stand-up comedian, writer, and actress known for her self-deprecating humor and roles in television and film comedies.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5ee97fd0819087ef8fe14b37ae43 |
completed | March 31, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf519f029081908ad0ae79f35b3e9d |
completed | April 3, 2026, 5:35 a.m. |
| NEDg | Description generation | batch_69cf560021148190b60f3f32b0a952b4 |
completed | April 3, 2026, 5:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf5654aa4c8190a368a0caca8ed45b |
completed | April 3, 2026, 5:55 a.m. |
Created at: March 30, 2026, 6:41 p.m.