Triple
T22390604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menudo |
E553500
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Miguel Cancel
Miguel Cancel is a Puerto Rican singer best known as a former member of the popular Latin boy band Menudo during its early 1980s heyday.
|
E1534612
|
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: Miguel Cancel | Statement: [Menudo, hasPart, Miguel Cancel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miguel Cancel Context triple: [Menudo, hasPart, Miguel Cancel]
-
A.
Miguel Lemos
Miguel Lemos was a Brazilian philosopher and leading positivist who co-founded and led the Brazilian Positivist Church, promoting Auguste Comte’s ideas in Brazil.
-
B.
Miguel Lemos
Miguel Lemos is a Brazilian designer credited with helping create the modern national flag of Brazil.
-
C.
Miguel Ordóñez
Miguel Ordóñez is an illustrator known for his playful, minimalist artwork in children’s books and other visual storytelling projects.
-
D.
Miguel Leon
Miguel Leon is the central protagonist of the film "The Last Face," a humanitarian doctor navigating love and moral conflict amid the chaos of war-torn Africa.
-
E.
Miguel Laurel
Miguel Laurel was a notable Filipino figure after whom the municipality of Laurel in Batangas, Philippines, was named.
- 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: Miguel Cancel Triple: [Menudo, hasPart, Miguel Cancel]
Generated description
Miguel Cancel is a Puerto Rican singer best known as a former member of the popular Latin boy band Menudo during its early 1980s heyday.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Miguel Cancel Target entity description: Miguel Cancel is a Puerto Rican singer best known as a former member of the popular Latin boy band Menudo during its early 1980s heyday.
-
A.
Miguel Lemos
Miguel Lemos is a Brazilian designer credited with helping create the modern national flag of Brazil.
-
B.
Miguel Lemos
Miguel Lemos was a Brazilian philosopher and leading positivist who co-founded and led the Brazilian Positivist Church, promoting Auguste Comte’s ideas in Brazil.
-
C.
Miguel Ordóñez
Miguel Ordóñez is an illustrator known for his playful, minimalist artwork in children’s books and other visual storytelling projects.
-
D.
Miguel Leon
Miguel Leon is the central protagonist of the film "The Last Face," a humanitarian doctor navigating love and moral conflict amid the chaos of war-torn Africa.
-
E.
Miguel Laurel
Miguel Laurel was a notable Filipino figure after whom the municipality of Laurel in Batangas, Philippines, was named.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15859853c8190b849cb34a94106da |
completed | April 29, 2026, 1:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae9c00c4c819093f9eb6b95964a6a |
completed | May 18, 2026, 10:28 a.m. |
| NEDg | Description generation | batch_6a0aead9d9cc8190ba7445bb8707ccf4 |
completed | May 18, 2026, 10:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0aeb6252248190a7cb0df06afd4db2 |
completed | May 18, 2026, 10:35 a.m. |
Created at: April 16, 2026, 8:45 p.m.