Triple
T18140027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Science of Sleep |
E434235
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Stéphanie
Stéphanie is a central character in the surreal romantic film "The Science of Sleep," known for her creative, whimsical personality and complex relationship with the dream-prone protagonist.
|
E1307924
|
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: Stéphanie | Statement: [The Science of Sleep, mainCharacter, Stéphanie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stéphanie Context triple: [The Science of Sleep, mainCharacter, Stéphanie]
-
A.
Stéphanie
Stéphanie is a Monegasque princess, singer, and fashion designer, best known as the youngest child of Prince Rainier III and Grace Kelly.
-
B.
Nathalie
Nathalie is a feminine given name of French origin commonly used in many European and French-speaking countries.
-
C.
Mélanie
Mélanie is a feminine given name of French origin commonly used in French-speaking countries.
-
D.
Sophie Dumond
Sophie Dumond is Arthur Fleck’s single-mother neighbor and tentative love interest in the 2019 film "Joker," representing his yearning for connection and normalcy amid his psychological unraveling.
-
E.
Léa
Léa is a French feminine given name commonly used in Francophone countries.
- 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: Stéphanie Triple: [The Science of Sleep, mainCharacter, Stéphanie]
Generated description
Stéphanie is a central character in the surreal romantic film "The Science of Sleep," known for her creative, whimsical personality and complex relationship with the dream-prone protagonist.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stéphanie Target entity description: Stéphanie is a central character in the surreal romantic film "The Science of Sleep," known for her creative, whimsical personality and complex relationship with the dream-prone protagonist.
-
A.
Stéphanie
Stéphanie is a Monegasque princess, singer, and fashion designer, best known as the youngest child of Prince Rainier III and Grace Kelly.
-
B.
Nathalie
Nathalie is a feminine given name of French origin commonly used in many European and French-speaking countries.
-
C.
Mélanie
Mélanie is a feminine given name of French origin commonly used in French-speaking countries.
-
D.
Sophie Dumond
Sophie Dumond is Arthur Fleck’s single-mother neighbor and tentative love interest in the 2019 film "Joker," representing his yearning for connection and normalcy amid his psychological unraveling.
-
E.
Léa
Léa is a French feminine given name commonly used in Francophone countries.
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de0a59d08190be74c1ecc00a8f3a |
completed | April 19, 2026, 1:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03854e76d8819082bae8d5f08e5992 |
completed | May 12, 2026, 7:53 p.m. |
| NEDg | Description generation | batch_6a038684e2908190ad31b29faabb4e46 |
completed | May 12, 2026, 7:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0386e3b51c81908c41fa719a4bf72f |
completed | May 12, 2026, 8 p.m. |
Created at: April 10, 2026, 10:29 a.m.