Triple
T7802942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ochoa |
E180474
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Carlos Ochoa
Carlos Ochoa is a personal name shared by multiple individuals, including professionals and public figures in various fields.
|
E717641
|
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: Carlos Ochoa | Statement: [Ochoa, hasNotableBearer, Carlos Ochoa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carlos Ochoa Context triple: [Ochoa, hasNotableBearer, Carlos Ochoa]
-
A.
Sergio Avelar
Sergio Avelar is an actor known for his role in the inspirational sports drama film "McFarland, USA."
-
B.
Luis Salmerón
Luis Salmerón is a former Argentine professional footballer known for his role as a forward with several clubs in South America.
-
C.
Horacio Gutiérrez
Horacio Gutiérrez is a Cuban-American classical pianist renowned for his virtuosic technique and interpretations of the Romantic repertoire.
-
D.
Reynaldo Villalobos
Reynaldo Villalobos is a cinematographer best known for his work on notable American films such as the comedy classic "9 to 5."
-
E.
Raúl Chávez
Raúl Chávez is a former Venezuelan professional baseball catcher who played in Major League Baseball, primarily known for his defensive skills behind the plate.
- 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: Carlos Ochoa Triple: [Ochoa, hasNotableBearer, Carlos Ochoa]
Generated description
Carlos Ochoa is a personal name shared by multiple individuals, including professionals and public figures in various fields.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Carlos Ochoa Target entity description: Carlos Ochoa is a personal name shared by multiple individuals, including professionals and public figures in various fields.
-
A.
Sergio Avelar
Sergio Avelar is an actor known for his role in the inspirational sports drama film "McFarland, USA."
-
B.
Luis Salmerón
Luis Salmerón is a former Argentine professional footballer known for his role as a forward with several clubs in South America.
-
C.
Horacio Gutiérrez
Horacio Gutiérrez is a Cuban-American classical pianist renowned for his virtuosic technique and interpretations of the Romantic repertoire.
-
D.
Reynaldo Villalobos
Reynaldo Villalobos is a cinematographer best known for his work on notable American films such as the comedy classic "9 to 5."
-
E.
Raúl Chávez
Raúl Chávez is a former Venezuelan professional baseball catcher who played in Major League Baseball, primarily known for his defensive skills behind the plate.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf635a4648190af907a686d87f073 |
completed | March 30, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccec40f5e88190bc0fbb4ad99d09c6 |
completed | April 1, 2026, 9:58 a.m. |
| NEDg | Description generation | batch_69ccf0982f4481908e2a59424fdf470f |
completed | April 1, 2026, 10:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd051913708190a83f925cf0cbbaa1 |
completed | April 1, 2026, 11:44 a.m. |
Created at: March 30, 2026, 4:34 p.m.