Triple
T9937236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eternals (film) |
E193988
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Kaz Firpo
Kaz Firpo is an American screenwriter best known for co-writing Marvel Studios' superhero ensemble film "Eternals."
|
E832841
|
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: Kaz Firpo | Statement: [Eternals (film), screenwriter, Kaz Firpo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaz Firpo Context triple: [Eternals (film), screenwriter, Kaz Firpo]
-
A.
Gus Molino
Gus Molino is the protagonist of the film "Sugar Hill," around whom the story’s central conflicts and developments revolve.
-
B.
Alvey Kulina
Alvey Kulina is a troubled former MMA fighter and gym owner who serves as the complex patriarchal figure in the television drama series "Kingdom."
-
C.
Tony Meola
Tony Meola is a former American soccer goalkeeper best known for starring with the U.S. national team in the 1990 and 1994 World Cups and for his standout career in Major League Soccer.
-
D.
Larry Marfise
Larry Marfise is a collegiate sports administrator best known for serving as the athletic director for the Spartans athletic program.
-
E.
Bernie Federko
Bernie Federko is a Hall of Fame Canadian center best known as a longtime offensive star and playmaker for the St. Louis Blues in the NHL.
- 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: Kaz Firpo Triple: [Eternals (film), screenwriter, Kaz Firpo]
Generated description
Kaz Firpo is an American screenwriter best known for co-writing Marvel Studios' superhero ensemble film "Eternals."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaz Firpo Target entity description: Kaz Firpo is an American screenwriter best known for co-writing Marvel Studios' superhero ensemble film "Eternals."
-
A.
Gus Molino
Gus Molino is the protagonist of the film "Sugar Hill," around whom the story’s central conflicts and developments revolve.
-
B.
Alvey Kulina
Alvey Kulina is a troubled former MMA fighter and gym owner who serves as the complex patriarchal figure in the television drama series "Kingdom."
-
C.
Tony Meola
Tony Meola is a former American soccer goalkeeper best known for starring with the U.S. national team in the 1990 and 1994 World Cups and for his standout career in Major League Soccer.
-
D.
Larry Marfise
Larry Marfise is a collegiate sports administrator best known for serving as the athletic director for the Spartans athletic program.
-
E.
Bernie Federko
Bernie Federko is a Hall of Fame Canadian center best known as a longtime offensive star and playmaker for the St. Louis Blues in the NHL.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e4e19881909879b394090d6629 |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23d4528108190b38111bb36832a67 |
completed | April 5, 2026, 10:45 a.m. |
| NEDg | Description generation | batch_69d23eb1c1f481908404225dcccd0697 |
completed | April 5, 2026, 10:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d242aea6a08190a73a836e59865c35 |
completed | April 5, 2026, 11:08 a.m. |
Created at: March 30, 2026, 8:44 p.m.