Triple
T10368162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Santa |
E244308
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Sue
Sue is a character from the dark comedy film "Bad Santa," known as the love interest of the main antihero, Willie T. Soke.
|
E858762
|
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: Sue | Statement: [Bad Santa, mainCharacter, Sue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sue Context triple: [Bad Santa, mainCharacter, Sue]
-
A.
Sue
Sue is the tough, resilient male protagonist of the humorous country song "A Boy Named Sue," whose life is shaped by the hardships caused by his traditionally feminine name.
-
B.
Sue
Sue is the given name of Sue Storm, the Invisible Woman and a central member of Marvel’s superhero team the Fantastic Four.
-
C.
Suzie
Suzie is a brilliant, tech-savvy girl from Stranger Things who helps Dustin Henderson and his friends by providing crucial scientific and hacking assistance.
-
D.
Suzanne
Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
-
E.
Suzanne
Suzanne is a feminine given name of French origin, derived from the Hebrew name Shoshannah meaning “lily.”
- 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: Sue Triple: [Bad Santa, mainCharacter, Sue]
Generated description
Sue is a character from the dark comedy film "Bad Santa," known as the love interest of the main antihero, Willie T. Soke.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sue Target entity description: Sue is a character from the dark comedy film "Bad Santa," known as the love interest of the main antihero, Willie T. Soke.
-
A.
Sue
Sue is the given name of Sue Storm, the Invisible Woman and a central member of Marvel’s superhero team the Fantastic Four.
-
B.
Sue
Sue is the tough, resilient male protagonist of the humorous country song "A Boy Named Sue," whose life is shaped by the hardships caused by his traditionally feminine name.
-
C.
Suzie
Suzie is a brilliant, tech-savvy girl from Stranger Things who helps Dustin Henderson and his friends by providing crucial scientific and hacking assistance.
-
D.
Suzanne
Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
-
E.
Suzanne
"Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e97106448190a075948e63184f47 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d79550b2ec8190ada086ddfeb398af |
completed | April 9, 2026, 12:02 p.m. |
| NEDg | Description generation | batch_69d7985e7fc081909fd1ba1dc6f7338c |
completed | April 9, 2026, 12:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d799917ab881909a947ad8059652c6 |
completed | April 9, 2026, 12:20 p.m. |
Created at: April 6, 2026, 12:01 p.m.