Triple
T22046995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magali Noël |
E544787
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Magali
Magali is the given name of French actress and singer Magali Noël, known for her roles in European cinema, particularly in Federico Fellini’s films.
|
E1517887
|
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: Magali | Statement: [Magali Noël, givenName, Magali]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magali Context triple: [Magali Noël, givenName, Magali]
-
A.
Manoela
Manoela is a feminine given name, commonly used in Portuguese- and Spanish-speaking countries, that is related to the name Manoel/Manuel.
-
B.
Noelia
Noelia is a feminine given name, commonly used in Spanish-speaking countries and derived from the name Noel.
-
C.
Nathalie
Nathalie is a feminine given name of French origin commonly used in many European and French-speaking countries.
-
D.
Marlen
Marlen is a village district of the town of Kehl in the German state of Baden-Württemberg.
-
E.
Marisabel
Marisabel is a feminine given name of Spanish origin, commonly used in Spanish-speaking 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: Magali Triple: [Magali Noël, givenName, Magali]
Generated description
Magali is the given name of French actress and singer Magali Noël, known for her roles in European cinema, particularly in Federico Fellini’s films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magali Target entity description: Magali is the given name of French actress and singer Magali Noël, known for her roles in European cinema, particularly in Federico Fellini’s films.
-
A.
Manoela
Manoela is a feminine given name, commonly used in Portuguese- and Spanish-speaking countries, that is related to the name Manoel/Manuel.
-
B.
Noelia
Noelia is a feminine given name, commonly used in Spanish-speaking countries and derived from the name Noel.
-
C.
Nathalie
Nathalie is a feminine given name of French origin commonly used in many European and French-speaking countries.
-
D.
Marlen
Marlen is a village district of the town of Kehl in the German state of Baden-Württemberg.
-
E.
Marisabel
Marisabel is a feminine given name of Spanish origin, commonly used in Spanish-speaking 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1282f4a448190bca55348c457a4bd |
completed | April 28, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a878d1db481908687fc86efe0547e |
completed | May 18, 2026, 3:29 a.m. |
| NEDg | Description generation | batch_6a0a88655b088190870c4ff9b6960c08 |
completed | May 18, 2026, 3:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a893b67f081909967ba88ce7922a0 |
completed | May 18, 2026, 3:36 a.m. |
Created at: April 16, 2026, 8:26 p.m.