Triple
T11049823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Come to Daddy |
E261215
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Blinder Films
Blinder Films is an Irish film and television production company known for producing independent and genre-bending features and series.
|
E901302
|
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: Blinder Films | Statement: [Come to Daddy, productionCompany, Blinder Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blinder Films Context triple: [Come to Daddy, productionCompany, Blinder Films]
-
A.
Shoebox Films
Shoebox Films is a British film production company known for producing independent and auteur-driven movies, including the 2019 thriller "Serenity."
-
B.
Skreba Films
Skreba Films is a film production company known for producing the biographical drama "Tom & Viv."
-
C.
Ombra Films
Ombra Films is a film production company known for working on action and thriller movies, including the crime thriller "Run All Night."
-
D.
Kestrel Films
Kestrel Films is a British film production company best known for producing Ken Loach’s acclaimed 1969 drama "Kes."
-
E.
Bloom Films
Bloom Films is a film production company known for producing the historical comedy-drama movie "Elvis & Nixon."
- 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: Blinder Films Triple: [Come to Daddy, productionCompany, Blinder Films]
Generated description
Blinder Films is an Irish film and television production company known for producing independent and genre-bending features and series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Blinder Films Target entity description: Blinder Films is an Irish film and television production company known for producing independent and genre-bending features and series.
-
A.
Shoebox Films
Shoebox Films is a British film production company known for producing independent and auteur-driven movies, including the 2019 thriller "Serenity."
-
B.
Skreba Films
Skreba Films is a film production company known for producing the biographical drama "Tom & Viv."
-
C.
Ombra Films
Ombra Films is a film production company known for working on action and thriller movies, including the crime thriller "Run All Night."
-
D.
Kestrel Films
Kestrel Films is a British film production company best known for producing Ken Loach’s acclaimed 1969 drama "Kes."
-
E.
Bloom Films
Bloom Films is a film production company known for producing the historical comedy-drama movie "Elvis & Nixon."
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79868c78881908c8e3672c05ae7ec |
completed | April 9, 2026, 12:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3aa06bae08190a0db615a258ded29 |
completed | April 18, 2026, 3:57 p.m. |
| NEDg | Description generation | batch_69e3ad0379888190b2f56d36d79bf97d |
completed | April 18, 2026, 4:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3b206c7a4819087eb06faa6e1af21 |
completed | April 18, 2026, 4:32 p.m. |
Created at: April 8, 2026, 9:26 p.m.