Triple
T16087139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniella Pineda |
E390261
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object |
Marina Hess
Marina Hess is a fictional character portrayed by actress Daniella Pineda, best known as a supporting role in contemporary film and television.
|
E1192425
|
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: Marina Hess | Statement: [Daniella Pineda, playedCharacter, Marina Hess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marina Hess Context triple: [Daniella Pineda, playedCharacter, Marina Hess]
-
A.
Marina Gefter
Marina Gefter is a film producer best known for her work on the movie "Femme Fatale."
-
B.
Marina Oswald
Marina Oswald is the Russian-born widow of Lee Harvey Oswald, the accused assassin of U.S. President John F. Kennedy, who became a notable figure in the aftermath of the 1963 assassination.
-
C.
Marina Solodkin
Marina Solodkin was a Russian-born Israeli politician and Knesset member known for advocating immigrant rights and social justice.
-
D.
Marina Wheeler
Marina Wheeler is a British barrister and writer, known for her work in public law and for her former marriage to politician Boris Johnson.
-
E.
Maria Cristina Heller
Maria Cristina Heller is an actress known for her role in the film "Walking on Sunshine."
- 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: Marina Hess Triple: [Daniella Pineda, playedCharacter, Marina Hess]
Generated description
Marina Hess is a fictional character portrayed by actress Daniella Pineda, best known as a supporting role in contemporary film and television.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marina Hess Target entity description: Marina Hess is a fictional character portrayed by actress Daniella Pineda, best known as a supporting role in contemporary film and television.
-
A.
Marina Gefter
Marina Gefter is a film producer best known for her work on the movie "Femme Fatale."
-
B.
Marina Oswald
Marina Oswald is the Russian-born widow of Lee Harvey Oswald, the accused assassin of U.S. President John F. Kennedy, who became a notable figure in the aftermath of the 1963 assassination.
-
C.
Marina Solodkin
Marina Solodkin was a Russian-born Israeli politician and Knesset member known for advocating immigrant rights and social justice.
-
D.
Marina Wheeler
Marina Wheeler is a British barrister and writer, known for her work in public law and for her former marriage to politician Boris Johnson.
-
E.
Maria Cristina Heller
Maria Cristina Heller is an actress known for her role in the film "Walking on Sunshine."
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1844f95508190a06dad0ccc9b6191 |
completed | April 17, 2026, 12:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe48ef3608190848d4730a4361395 |
completed | May 10, 2026, 1:51 a.m. |
| NEDg | Description generation | batch_69ffe5bed55c8190a159bae35fe140d0 |
completed | May 10, 2026, 1:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffe62e66608190a88e2815a9a9be04 |
completed | May 10, 2026, 1:58 a.m. |
Created at: April 10, 2026, 4:59 a.m.