Triple
T4098747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moulin Rouge! The Musical |
E87886
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Satine
Satine is the glamorous star courtesan and tragic heroine at the heart of the romantic story in Moulin Rouge! The Musical.
|
E412729
|
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: Satine | Statement: [Moulin Rouge! The Musical, featuresCharacter, Satine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satine Context triple: [Moulin Rouge! The Musical, featuresCharacter, Satine]
-
A.
Mireille
Mireille is a five-act French opera by Charles Gounod, based on Frédéric Mistral’s Provençal poem "Mirèio."
-
B.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
C.
Odile
Odile is the seductive and deceptive Black Swan character in the ballet "Swan Lake," often portrayed as the antagonist and foil to the virtuous Odette.
-
D.
Margaux
Margaux is a prestigious Bordeaux wine appellation in the Médoc region of France, renowned for its elegant, aromatic red wines and several classified growth châteaux.
-
E.
Malena
Malena is a feminine given name, commonly used in various cultures and often considered a diminutive or variant of names like Magdalena.
- 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: Satine Triple: [Moulin Rouge! The Musical, featuresCharacter, Satine]
Generated description
Satine is the glamorous star courtesan and tragic heroine at the heart of the romantic story in Moulin Rouge! The Musical.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Satine Target entity description: Satine is the glamorous star courtesan and tragic heroine at the heart of the romantic story in Moulin Rouge! The Musical.
-
A.
Mireille
Mireille is a five-act French opera by Charles Gounod, based on Frédéric Mistral’s Provençal poem "Mirèio."
-
B.
Rosabella
Rosabella is the shy, kind-hearted waitress who becomes the central romantic heroine in Frank Loesser’s Broadway musical "The Most Happy Fella."
-
C.
Odile
Odile is the seductive and deceptive Black Swan character in the ballet "Swan Lake," often portrayed as the antagonist and foil to the virtuous Odette.
-
D.
Margaux
Margaux is a prestigious Bordeaux wine appellation in the Médoc region of France, renowned for its elegant, aromatic red wines and several classified growth châteaux.
-
E.
Malena
Malena is a feminine given name, commonly used in various cultures and often considered a diminutive or variant of names like Magdalena.
- 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_69aed94564cc8190a9c1457daedb6e7f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0bdea48190805a79515ee92709 |
completed | March 9, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b7585bc81909dc2c02e60a55def |
completed | March 14, 2026, 2:06 p.m. |
| NEDg | Description generation | batch_69b56c3a4b708190a55027fd3b2b76e0 |
completed | March 14, 2026, 2:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b56cc5c704819083dac59bf7b3cb83 |
completed | March 14, 2026, 2:12 p.m. |
Created at: March 9, 2026, 3:40 p.m.