Triple
T4035119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Truman Show |
E83809
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Sylvia
Sylvia is a key character in the film "The Truman Show," a woman who tries to reveal the truth to Truman about his manufactured reality and becomes his inspiration to escape.
|
E407812
|
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: Sylvia | Statement: [The Truman Show, character, Sylvia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylvia Context triple: [The Truman Show, character, Sylvia]
-
A.
Sylvia
Sylvia is a feminine given name of Latin origin meaning "from the forest" or "of the woods."
-
B.
Sylvia’s
Sylvia’s is a famed soul food restaurant in Harlem, New York City, renowned for its Southern cuisine and cultural significance in the neighborhood.
-
C.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
-
D.
Suzanne
"Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
-
E.
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.
- 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: Sylvia Triple: [The Truman Show, character, Sylvia]
Generated description
Sylvia is a key character in the film "The Truman Show," a woman who tries to reveal the truth to Truman about his manufactured reality and becomes his inspiration to escape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sylvia Target entity description: Sylvia is a key character in the film "The Truman Show," a woman who tries to reveal the truth to Truman about his manufactured reality and becomes his inspiration to escape.
-
A.
Sylvia
Sylvia is a feminine given name of Latin origin meaning "from the forest" or "of the woods."
-
B.
Sylvia’s
Sylvia’s is a famed soul food restaurant in Harlem, New York City, renowned for its Southern cuisine and cultural significance in the neighborhood.
-
C.
Lila
Lila is a central female character in Max Frisch’s novel "Mein Name sei Gantenbein," around whom the narrator constructs one of his imagined lives and relationships.
-
D.
Suzanne
"Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
-
E.
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.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb11d92481909aaebbc250ff45b9 |
completed | March 9, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b556415ebc8190a528c7e22dbf70df |
completed | March 14, 2026, 12:36 p.m. |
| NEDg | Description generation | batch_69b556efc2148190a66e732e09e4fc21 |
completed | March 14, 2026, 12:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5575de0e88190843f1fcbc12c9dd5 |
completed | March 14, 2026, 12:41 p.m. |
Created at: March 9, 2026, 3:36 p.m.