Triple
T18081832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand |
E432708
|
entity |
| Predicate | storyBy |
P1955
|
FINISHED |
| Object |
Ron Burch
Ron Burch is an American writer and screenwriter known for his work in film and television, including co-writing the animated feature "Ferdinand."
|
E1316593
|
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: Ron Burch | Statement: [Ferdinand, storyBy, Ron Burch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ron Burch Context triple: [Ferdinand, storyBy, Ron Burch]
-
A.
Don Burnett
Don Burnett was a British-born American actor best known for his film and television roles in the 1950s and 1960s.
-
B.
Bill Boals
Bill Boals is the husband of American character actress Margo Martindale.
-
C.
Phil Dusenberry
Phil Dusenberry was an influential American advertising executive and creative director, best known for his groundbreaking work at BBDO and for shaping major campaigns for brands like Pepsi.
-
D.
Don Saleski
Don Saleski is a former NHL right winger best known for his gritty, physical play with the Philadelphia Flyers during their 1970s "Broad Street Bullies" era.
-
E.
Byron Bowers
Byron Bowers is an American stand-up comedian, writer, and actor known for his work in television, film, and comedy specials.
- 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: Ron Burch Triple: [Ferdinand, storyBy, Ron Burch]
Generated description
Ron Burch is an American writer and screenwriter known for his work in film and television, including co-writing the animated feature "Ferdinand."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ron Burch Target entity description: Ron Burch is an American writer and screenwriter known for his work in film and television, including co-writing the animated feature "Ferdinand."
-
A.
Don Burnett
Don Burnett was a British-born American actor best known for his film and television roles in the 1950s and 1960s.
-
B.
Bill Boals
Bill Boals is the husband of American character actress Margo Martindale.
-
C.
Phil Dusenberry
Phil Dusenberry was an influential American advertising executive and creative director, best known for his groundbreaking work at BBDO and for shaping major campaigns for brands like Pepsi.
-
D.
Don Saleski
Don Saleski is a former NHL right winger best known for his gritty, physical play with the Philadelphia Flyers during their 1970s "Broad Street Bullies" era.
-
E.
Byron Bowers
Byron Bowers is an American stand-up comedian, writer, and actor known for his work in television, film, and comedy specials.
- 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9fb42888190919fe711a281bd7c |
completed | April 19, 2026, 1:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03bb437384819099d5e51ae9151786 |
completed | May 12, 2026, 11:44 p.m. |
| NEDg | Description generation | batch_6a03bbfa0da481908bb0e388dcbe9913 |
completed | May 12, 2026, 11:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03bd6078b88190887a32099fc31db0 |
completed | May 12, 2026, 11:53 p.m. |
Created at: April 10, 2026, 10:27 a.m.