Triple
T7561138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinsey |
E178795
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Myriad Pictures
Myriad Pictures is an independent film production and distribution company known for handling a range of arthouse and specialty films.
|
E676650
|
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: Myriad Pictures | Statement: [Kinsey, productionCompany, Myriad Pictures]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myriad Pictures Context triple: [Kinsey, productionCompany, Myriad Pictures]
-
A.
Troika Pictures
Troika Pictures is a film production company known for producing feature films such as the thriller "The Call" (2013).
-
B.
Magnolia Pictures
Magnolia Pictures is an American independent film distribution company known for releasing a wide range of arthouse, documentary, and foreign films.
-
C.
Vistar Films
Vistar Films is a film production company best known for its involvement in the making of the 1985 horror-comedy classic "Fright Night."
-
D.
Horizon Pictures
Horizon Pictures is a film production company best known for producing the epic historical drama "Lawrence of Arabia."
-
E.
Keystone Pictures
Keystone Pictures is a film production company best known for producing the family sports comedy movie "Air Bud."
- 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: Myriad Pictures Triple: [Kinsey, productionCompany, Myriad Pictures]
Generated description
Myriad Pictures is an independent film production and distribution company known for handling a range of arthouse and specialty films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Myriad Pictures Target entity description: Myriad Pictures is an independent film production and distribution company known for handling a range of arthouse and specialty films.
-
A.
Troika Pictures
Troika Pictures is a film production company known for producing feature films such as the thriller "The Call" (2013).
-
B.
Magnolia Pictures
Magnolia Pictures is an American independent film distribution company known for releasing a wide range of arthouse, documentary, and foreign films.
-
C.
Vistar Films
Vistar Films is a film production company best known for its involvement in the making of the 1985 horror-comedy classic "Fright Night."
-
D.
Horizon Pictures
Horizon Pictures is a film production company best known for producing the epic historical drama "Lawrence of Arabia."
-
E.
Keystone Pictures
Keystone Pictures is a film production company best known for producing the family sports comedy movie "Air Bud."
- 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_69c69f2f80288190b95cceb4da92ab2b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8f847c48190a1081aa9de7ff945 |
completed | March 27, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8683978b48190971b4c38fd83d3cc |
completed | March 28, 2026, 11:46 p.m. |
| NEDg | Description generation | batch_69c869588d008190adc28df91a99f09f |
completed | March 28, 2026, 11:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c86a1f1bfc8190b25597a030613e08 |
completed | March 28, 2026, 11:54 p.m. |
Created at: March 27, 2026, 3:50 p.m.