Triple
T7865881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magaña |
E182612
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Ángel Magaña
Ángel Magaña was an Argentine film and theater actor known for his prominent roles in classic Argentine cinema during the mid-20th century.
|
E734046
|
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: Ángel Magaña | Statement: [Magaña, hasNotableBearer, Ángel Magaña]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ángel Magaña Context triple: [Magaña, hasNotableBearer, Ángel Magaña]
-
A.
Guillermo Magaña
Guillermo Magaña is a person notable enough to be recognized as a bearer of the surname Magaña, though specific widely known public details about him are not clearly established.
-
B.
Miguel Briseño
Miguel Briseño is a musician best known as a member of the American indie folk band Lord Huron.
-
C.
Armando Villarreal
Armando Villarreal is an American professional soccer referee who officiates in Major League Soccer and has been selected for high-profile matches and tournaments.
-
D.
Sergio Avelar
Sergio Avelar is an actor known for his role in the inspirational sports drama film "McFarland, USA."
-
E.
Enrique Arce
Enrique Arce is a Spanish actor best known internationally for his role as the unscrupulous Arturo Román in the hit series "Money Heist."
- 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: Ángel Magaña Triple: [Magaña, hasNotableBearer, Ángel Magaña]
Generated description
Ángel Magaña was an Argentine film and theater actor known for his prominent roles in classic Argentine cinema during the mid-20th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ángel Magaña Target entity description: Ángel Magaña was an Argentine film and theater actor known for his prominent roles in classic Argentine cinema during the mid-20th century.
-
A.
Guillermo Magaña
Guillermo Magaña is a person notable enough to be recognized as a bearer of the surname Magaña, though specific widely known public details about him are not clearly established.
-
B.
Miguel Briseño
Miguel Briseño is a musician best known as a member of the American indie folk band Lord Huron.
-
C.
Armando Villarreal
Armando Villarreal is an American professional soccer referee who officiates in Major League Soccer and has been selected for high-profile matches and tournaments.
-
D.
Sergio Avelar
Sergio Avelar is an actor known for his role in the inspirational sports drama film "McFarland, USA."
-
E.
Enrique Arce
Enrique Arce is a Spanish actor best known internationally for his role as the unscrupulous Arturo Román in the hit series "Money Heist."
- 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_69ca82894d9081908a832bfce71a4714 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3844eacc81908f8e1e5fc4dafec8 |
completed | March 31, 2026, 2:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1c56d07481909083f028b2b5673f |
completed | April 2, 2026, 7:35 a.m. |
| NEDg | Description generation | batch_69ce1e3a269481908ea191ff28ea1313 |
completed | April 2, 2026, 7:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce1ef9fb208190a50b4d8a595f5fdb |
completed | April 2, 2026, 7:47 a.m. |
Created at: March 30, 2026, 4:54 p.m.