Triple
T1769048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magdalena |
E38830
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Maddalena
Maddalena is the Italian form of the given name Magdalena, traditionally associated with Mary Magdalene in Christian tradition.
|
E201622
|
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: Maddalena | Statement: [Magdalena, hasVariant, Maddalena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maddalena Context triple: [Magdalena, hasVariant, Maddalena]
-
A.
Madalena
Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
-
B.
Leonora
Leonora is a feminine given name used in various cultures, often considered a variant of Eleanor or Leonore.
-
C.
Caterina
Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
-
D.
Adelaide del Vasto
Adelaide del Vasto was a Norman noblewoman who served as regent of Sicily and later became queen consort of Jerusalem in the early 12th century.
-
E.
Ludovica
Ludovica is an Italian feminine given name, traditionally associated with nobility and derived from the same Germanic roots as names like Louise and Ludwig.
- 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: Maddalena Triple: [Magdalena, hasVariant, Maddalena]
Generated description
Maddalena is the Italian form of the given name Magdalena, traditionally associated with Mary Magdalene in Christian tradition.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maddalena Target entity description: Maddalena is the Italian form of the given name Magdalena, traditionally associated with Mary Magdalene in Christian tradition.
-
A.
Madalena
Madalena is a neighborhood in the Brazilian city of Recife, known for its urban character and local commerce.
-
B.
Leonora
Leonora is a feminine given name used in various cultures, often considered a variant of Eleanor or Leonore.
-
C.
Caterina
Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
-
D.
Adelaide del Vasto
Adelaide del Vasto was a Norman noblewoman who served as regent of Sicily and later became queen consort of Jerusalem in the early 12th century.
-
E.
Ludovica
Ludovica is an Italian feminine given name, traditionally associated with nobility and derived from the same Germanic roots as names like Louise and Ludwig.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa648d9f2c8190aca4884648a69eb0 |
completed | March 6, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5c727e48190b934e9b97b084c7a |
completed | March 8, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69adb8b3c0a48190bf5f3a32d8862c54 |
completed | March 8, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb97b8c8081909a806d16efd5882b |
completed | March 8, 2026, 6:01 p.m. |
Created at: March 4, 2026, 7:31 p.m.