Triple
T5293915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blade Runner 2049 |
E119808
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Cynthia Yorkin
Cynthia Yorkin is a film producer best known for her work on the science fiction sequel "Blade Runner 2049."
|
E517262
|
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: Cynthia Yorkin | Statement: [Blade Runner 2049, producer, Cynthia Yorkin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cynthia Yorkin Context triple: [Blade Runner 2049, producer, Cynthia Yorkin]
-
A.
Cynthia Blaise
Cynthia Blaise is an American dialect coach and actress known for her work on films such as "Bad Teacher" and "The Tiger Hunter."
-
B.
Cynthia Stone
Cynthia Stone was an American actress best known for her work in early television and for her marriage to actor Jack Lemmon.
-
C.
Cynthia Mort
Cynthia Mort is an American screenwriter, director, and producer known for her work in film and television, including projects like "The Brave One" and the biographical drama "Nina."
-
D.
Cynthia Stevenson
Cynthia Stevenson is an American actress known for her work in film and television, including roles in projects like "Home for the Holidays" and the series "Dead Like Me."
-
E.
Cindy Morgan
Cindy Morgan is an American actress best known for her roles in the comedy film "Caddyshack" and the science fiction film "Tron."
- 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: Cynthia Yorkin Triple: [Blade Runner 2049, producer, Cynthia Yorkin]
Generated description
Cynthia Yorkin is a film producer best known for her work on the science fiction sequel "Blade Runner 2049."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cynthia Yorkin Target entity description: Cynthia Yorkin is a film producer best known for her work on the science fiction sequel "Blade Runner 2049."
-
A.
Cynthia Blaise
Cynthia Blaise is an American dialect coach and actress known for her work on films such as "Bad Teacher" and "The Tiger Hunter."
-
B.
Cynthia Stone
Cynthia Stone was an American actress best known for her work in early television and for her marriage to actor Jack Lemmon.
-
C.
Cynthia Mort
Cynthia Mort is an American screenwriter, director, and producer known for her work in film and television, including projects like "The Brave One" and the biographical drama "Nina."
-
D.
Cynthia Stevenson
Cynthia Stevenson is an American actress known for her work in film and television, including roles in projects like "Home for the Holidays" and the series "Dead Like Me."
-
E.
Cindy Morgan
Cindy Morgan is an American actress best known for her roles in the comedy film "Caddyshack" and the science fiction film "Tron."
- 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_69bd446f22b88190b6a47fb91c68a3e7 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd84f034f081908027a43120b6e122 |
completed | March 20, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf33248cf481908eeb0abd3b1a7828 |
completed | March 22, 2026, 12:09 a.m. |
| NEDg | Description generation | batch_69bf33e3b9ac819091cb000a98a505cd |
completed | March 22, 2026, 12:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf349a746481909a8ba2a854e29449 |
completed | March 22, 2026, 12:15 a.m. |
Created at: March 20, 2026, 1:52 p.m.