Triple
T6101516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nurses (U.S. TV series) |
E136007
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Gina Cuevas
Gina Cuevas is a fictional character appearing in the American medical drama television series "Nurses."
|
E577306
|
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: Gina Cuevas | Statement: [Nurses (U.S. TV series), character, Gina Cuevas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gina Cuevas Context triple: [Nurses (U.S. TV series), character, Gina Cuevas]
-
A.
Rachel Salas
Rachel Salas is a central character in the science-fiction film "In Time," portrayed as the wealthy and protective mother of Sylvia Weis.
-
B.
Mayte Garcia
Mayte Garcia is an American dancer, choreographer, and actress best known for her work with and marriage to the musician Prince.
-
C.
JoAnna Garcia
JoAnna Garcia is an American actress known for her roles in television series such as "Reba," "Privileged," and "Sweet Magnolias."
-
D.
Aimee Garcia
Aimee Garcia is an American actress best known for her television roles on shows like "Dexter" and "Lucifer," as well as her work in film and voice acting.
-
E.
Melissa Navia
Melissa Navia is an American actress best known for her role as Lt. Erica Ortegas on the television series "Star Trek: Strange New Worlds."
- 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: Gina Cuevas Triple: [Nurses (U.S. TV series), character, Gina Cuevas]
Generated description
Gina Cuevas is a fictional character appearing in the American medical drama television series "Nurses."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gina Cuevas Target entity description: Gina Cuevas is a fictional character appearing in the American medical drama television series "Nurses."
-
A.
Rachel Salas
Rachel Salas is a central character in the science-fiction film "In Time," portrayed as the wealthy and protective mother of Sylvia Weis.
-
B.
Mayte Garcia
Mayte Garcia is an American dancer, choreographer, and actress best known for her work with and marriage to the musician Prince.
-
C.
JoAnna Garcia
JoAnna Garcia is an American actress known for her roles in television series such as "Reba," "Privileged," and "Sweet Magnolias."
-
D.
Aimee Garcia
Aimee Garcia is an American actress best known for her television roles on shows like "Dexter" and "Lucifer," as well as her work in film and voice acting.
-
E.
Melissa Navia
Melissa Navia is an American actress best known for her role as Lt. Erica Ortegas on the television series "Star Trek: Strange New Worlds."
- 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_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3aa9908190865be98ada141d37 |
completed | March 22, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20d56f234819082d89a755ae5a446 |
completed | March 24, 2026, 4:04 a.m. |
| NEDg | Description generation | batch_69c216517d2c8190bf242c2e19bf5dd0 |
completed | March 24, 2026, 4:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c216bdd3ac819087458b76791eebfa |
completed | March 24, 2026, 4:44 a.m. |
Created at: March 22, 2026, 4:13 p.m.