Triple
T9983978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nash Bridges |
E196519
|
entity |
| Predicate | supportingCharacter |
P7748
|
FINISHED |
| Object |
Joe Dominguez
Joe Dominguez is a retired police inspector and humorous, streetwise sidekick to the title character on the television series "Nash Bridges."
|
E869206
|
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: Joe Dominguez | Statement: [Nash Bridges, supportingCharacter, Joe Dominguez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Dominguez Context triple: [Nash Bridges, supportingCharacter, Joe Dominguez]
-
A.
Frank Dominguez
Frank Dominguez is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
B.
Frank Dominguez
Frank Dominguez is an entrepreneur best known as a founder of the cloud-based software company Salesforce.
-
C.
Greg Giraldo
Greg Giraldo was an American stand-up comedian and television personality known for his sharp, acerbic wit and frequent appearances on Comedy Central roasts and panel shows.
-
D.
Hector Duran
Hector Duran is an American actor best known for his role as one of the young runners in the inspirational sports drama film "McFarland, USA."
-
E.
Carlos Rios
Carlos Rios is a music producer best known for his work on the hit album "Can't Slow Down."
- 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: Joe Dominguez Triple: [Nash Bridges, supportingCharacter, Joe Dominguez]
Generated description
Joe Dominguez is a retired police inspector and humorous, streetwise sidekick to the title character on the television series "Nash Bridges."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Joe Dominguez Target entity description: Joe Dominguez is a retired police inspector and humorous, streetwise sidekick to the title character on the television series "Nash Bridges."
-
A.
Frank Dominguez
Frank Dominguez is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
B.
Frank Dominguez
Frank Dominguez is an entrepreneur best known as a founder of the cloud-based software company Salesforce.
-
C.
Greg Giraldo
Greg Giraldo was an American stand-up comedian and television personality known for his sharp, acerbic wit and frequent appearances on Comedy Central roasts and panel shows.
-
D.
Hector Duran
Hector Duran is an American actor best known for his role as one of the young runners in the inspirational sports drama film "McFarland, USA."
-
E.
Carlos Rios
Carlos Rios is a music producer best known for his work on the hit album "Can't Slow Down."
- 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb8bdc0388190bbbd4bdc5ac3adec |
completed | April 2, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90d54c32c8190b175a30c7c905cd2 |
completed | April 10, 2026, 2:46 p.m. |
| NEDg | Description generation | batch_69d9107c75108190994939ab46aa642f |
completed | April 10, 2026, 3 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9154c922c81909991f87f89c083cd |
completed | April 10, 2026, 3:20 p.m. |
Created at: March 30, 2026, 8:49 p.m.