Triple
T8408937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauricio Macri |
E198571
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Antonia Macri
Antonia Macri is the daughter of Argentine businessman and former president Mauricio Macri.
|
E731447
|
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: Antonia Macri | Statement: [Mauricio Macri, child, Antonia Macri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antonia Macri Context triple: [Mauricio Macri, child, Antonia Macri]
-
A.
Lucia Migliaccio
Lucia Migliaccio was an Italian noblewoman and duchess best known as the morganatic second wife of King Ferdinand I of the Two Sicilies.
-
B.
Sofia Villani Scicolone
Sofia Villani Scicolone is the birth name of Sophia Loren, the iconic Italian actress and international film star.
-
C.
Claudia Squitieri
Claudia Squitieri is the daughter of renowned Italian actress Claudia Cardinale and Italian film director Pasquale Squitieri.
-
D.
Carla Juri
Carla Juri is a Swiss actress known for her roles in European cinema and major international films, including the science fiction sequel Blade Runner 2049.
-
E.
Lucía Vanvitelli
Lucía Vanvitelli was the wife of Italian architect Francesco Sabatini, connecting her to the prominent Vanvitelli family of architects active in 18th-century Italy.
- 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: Antonia Macri Triple: [Mauricio Macri, child, Antonia Macri]
Generated description
Antonia Macri is the daughter of Argentine businessman and former president Mauricio Macri.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Antonia Macri Target entity description: Antonia Macri is the daughter of Argentine businessman and former president Mauricio Macri.
-
A.
Lucia Migliaccio
Lucia Migliaccio was an Italian noblewoman and duchess best known as the morganatic second wife of King Ferdinand I of the Two Sicilies.
-
B.
Sofia Villani Scicolone
Sofia Villani Scicolone is the birth name of Sophia Loren, the iconic Italian actress and international film star.
-
C.
Claudia Squitieri
Claudia Squitieri is the daughter of renowned Italian actress Claudia Cardinale and Italian film director Pasquale Squitieri.
-
D.
Carla Juri
Carla Juri is a Swiss actress known for her roles in European cinema and major international films, including the science fiction sequel Blade Runner 2049.
-
E.
Lucía Vanvitelli
Lucía Vanvitelli was the wife of Italian architect Francesco Sabatini, connecting her to the prominent Vanvitelli family of architects active in 18th-century Italy.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb8317045c8190b69cc99854b633be |
completed | March 31, 2026, 8:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce030dccf08190a70c0abf0bdcf244 |
completed | April 2, 2026, 5:47 a.m. |
| NEDg | Description generation | batch_69ce07808098819087e896b87320aefd |
completed | April 2, 2026, 6:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce08759e1c81909c96caf3b571e1ca |
completed | April 2, 2026, 6:11 a.m. |
Created at: March 30, 2026, 6:05 p.m.