Triple
T11136318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Dalton |
E263420
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object |
Roberto Ávila
Roberto Ávila is a fictional character portrayed by actor Tony Dalton, best known from the Mexican crime drama series "Sr. Ávila."
|
E976832
|
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: Roberto Ávila | Statement: [Tony Dalton, playedCharacter, Roberto Ávila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roberto Ávila Context triple: [Tony Dalton, playedCharacter, Roberto Ávila]
-
A.
José Ángel Romo
José Ángel Romo is a Mexican former professional footballer known for playing as a forward in Liga MX and other domestic leagues.
-
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.
Sergio Avelar
Sergio Avelar is an actor known for his role in the inspirational sports drama film "McFarland, USA."
-
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.
Carlos Ochoa
Carlos Ochoa is a personal name shared by multiple individuals, including professionals and public figures in various fields.
- 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: Roberto Ávila Triple: [Tony Dalton, playedCharacter, Roberto Ávila]
Generated description
Roberto Ávila is a fictional character portrayed by actor Tony Dalton, best known from the Mexican crime drama series "Sr. Ávila."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Roberto Ávila Target entity description: Roberto Ávila is a fictional character portrayed by actor Tony Dalton, best known from the Mexican crime drama series "Sr. Ávila."
-
A.
José Ángel Romo
José Ángel Romo is a Mexican former professional footballer known for playing as a forward in Liga MX and other domestic leagues.
-
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.
Sergio Avelar
Sergio Avelar is an actor known for his role in the inspirational sports drama film "McFarland, USA."
-
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.
Carlos Ochoa
Carlos Ochoa is a personal name shared by multiple individuals, including professionals and public figures in various fields.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e85daddc8190a1ae2a4a75cc8d50 |
completed | April 9, 2026, 5:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a6efa448190a9d95c5bd68ff34b |
completed | May 2, 2026, 4:46 p.m. |
| NEDg | Description generation | batch_69f62be354a88190aaf5e8439b33120b |
completed | May 2, 2026, 4:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62c8194d881909db3d320a21f2052 |
completed | May 2, 2026, 4:55 p.m. |
Created at: April 8, 2026, 9:28 p.m.