Triple
T13786912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urban Cowboy |
E331282
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Sissy
Sissy is the spirited, independent love interest of Bud Davis in the 1980 romantic Western film "Urban Cowboy."
|
E1062385
|
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: Sissy | Statement: [Urban Cowboy, mainCharacter, Sissy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sissy Context triple: [Urban Cowboy, mainCharacter, Sissy]
-
A.
Sissy
Sissy is a fictional character from the horror film "The Grave," known for her involvement in the movie’s dark, suspenseful storyline.
-
B.
Sissy Jupe
Sissy Jupe is a compassionate, imaginative young girl in Charles Dickens's novel "Hard Times," whose warmth and emotional intelligence contrast sharply with the book’s rigid, utilitarian society.
-
C.
Prissy
Prissy is a young enslaved house servant in Margaret Mitchell’s novel "Gone with the Wind," known for her fearful demeanor and memorable lines in the story.
-
D.
Prissy
Prissy is a diminutive nickname for the given name Priscilla, often used as an affectionate or informal form.
-
E.
Sissy St. Claire
Sissy St. Claire is the glittering, emotionally volatile variety-show host at the center of the surreal film "Give Me Pity!," embodying themes of fame, loneliness, and performance.
- 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: Sissy Triple: [Urban Cowboy, mainCharacter, Sissy]
Generated description
Sissy is the spirited, independent love interest of Bud Davis in the 1980 romantic Western film "Urban Cowboy."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sissy Target entity description: Sissy is the spirited, independent love interest of Bud Davis in the 1980 romantic Western film "Urban Cowboy."
-
A.
Sissy
Sissy is a fictional character from the horror film "The Grave," known for her involvement in the movie’s dark, suspenseful storyline.
-
B.
Sissy Jupe
Sissy Jupe is a compassionate, imaginative young girl in Charles Dickens's novel "Hard Times," whose warmth and emotional intelligence contrast sharply with the book’s rigid, utilitarian society.
-
C.
Prissy
Prissy is a young enslaved house servant in Margaret Mitchell’s novel "Gone with the Wind," known for her fearful demeanor and memorable lines in the story.
-
D.
Prissy
Prissy is a diminutive nickname for the given name Priscilla, often used as an affectionate or informal form.
-
E.
Sissy St. Claire
Sissy St. Claire is the glittering, emotionally volatile variety-show host at the center of the surreal film "Give Me Pity!," embodying themes of fame, loneliness, and performance.
- 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0249e4f88190a80316394940627d |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b07d872c81908f912263d8f7c80d |
completed | May 3, 2026, 8:30 p.m. |
| NEDg | Description generation | batch_69f7b230fb448190bc16a1d8732ff76f |
completed | May 3, 2026, 8:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7b2c55e188190b0ea8fa400ff2dfc |
completed | May 3, 2026, 8:40 p.m. |
Created at: April 9, 2026, 10:11 p.m.