Triple
T17247736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Duke |
E418669
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Neon Films
Neon Films is a British film production company known for producing independent and arthouse films, including the acclaimed drama "The Duke."
|
E1259232
|
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: Neon Films | Statement: [The Duke, productionCompany, Neon Films]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neon Films Context triple: [The Duke, productionCompany, Neon Films]
-
A.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
B.
Katalyst Films
Katalyst Films is a production company co-founded by Ashton Kutcher, best known for creating and producing popular prank and reality television shows and digital media content.
-
C.
Axon Films
Axon Films is a film production company known for producing the movie "Milk."
-
D.
Scion Films
Scion Films is a British film production company known for backing acclaimed dramas such as "The Constant Gardener."
-
E.
Overture Films
Overture Films was an American independent film production and distribution company active in the late 2000s, known for releasing a range of mid-budget and specialty films.
- 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: Neon Films Triple: [The Duke, productionCompany, Neon Films]
Generated description
Neon Films is a British film production company known for producing independent and arthouse films, including the acclaimed drama "The Duke."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Neon Films Target entity description: Neon Films is a British film production company known for producing independent and arthouse films, including the acclaimed drama "The Duke."
-
A.
Cinelou Films
Cinelou Films is an independent American film production company known for producing character-driven dramas such as the 2014 film "Cake."
-
B.
Katalyst Films
Katalyst Films is a production company co-founded by Ashton Kutcher, best known for creating and producing popular prank and reality television shows and digital media content.
-
C.
Axon Films
Axon Films is a film production company known for producing the movie "Milk."
-
D.
Scion Films
Scion Films is a British film production company known for backing acclaimed dramas such as "The Constant Gardener."
-
E.
Overture Films
Overture Films was an American independent film production and distribution company active in the late 2000s, known for releasing a range of mid-budget and specialty films.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e2569c081908ffd3ee9c76bcc17 |
completed | April 19, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170f744d8819099f10bbba364586d |
completed | May 11, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a01726ae14081909d11434e378d3e1c |
completed | May 11, 2026, 6:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a017525d8108190b2fff7d96beff345 |
completed | May 11, 2026, 6:20 a.m. |
Created at: April 10, 2026, 5:39 a.m.